Dissertations / Theses: 'Spline Function'

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Wang, Lu. "Cure Rate Model with Spline Estimated Components." Diss., Virginia Tech, 2010. http://hdl.handle.net/10919/28359.

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In some survival analysis of medical studies, there are often long term survivors who can be considered as permanently cured. The goals in these studies are to estimate the cure probability of the whole population and the hazard rate of the noncured subpopulation. The existing methods for cure rate models have been limited to parametric and semiparametric models. More specifically, the hazard function part is estimated by parametric or semiparametric model where the effect of covariate takes a parametric form. And the cure rate part is often estimated by a parametric logistic regression model. We introduce a non-parametric model employing smoothing splines. It provides non-parametric smooth estimates for both hazard function and cure rate. By introducing a latent cure status variable, we implement the method using a smooth EM algorithm. Louisâ formula for covariance estimation in an EM algorithm is generalized to yield point-wise confidence intervals for both functions. A simple model selection procedure based on the Kullback-Leibler geometry is derived for the proposed cure rate model. Numerical studies demonstrate excellent performance of the proposed method in estimation, inference and model selection. The application of the method is illustrated by the analysis of a melanoma study.
Ph. D.

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Kulkarni, Rekha Panditrao. "Fonctions spline cardinales tronquées." Grenoble 1, 1985. http://tel.archives-ouvertes.fr/tel-00318472.

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On propose des conditions de bout pour les fonctions spines polynomiales d'interpolation de degré p (p≥2) associées aux abscisses équidistantes qui économisent le calcul et entraînent un ordre de convergence optimal. Cette fonction spline peut être interprétée comme une fonction spline cardinale tronquée avec une correction convenable. La technique utilisée pour les fonctions splines polynomiales est applicable dans le cas des fonctions splines sous tension. On donne aussi quelques résultats pour les fonctions splines cubiques de lissage
On propose des conditions de bout pour les fonctions spines polynomiales d'interpolation de degre p (p >ou= 2) associees aux abscisses equidistantes qui economisent le calcul et entrainent un ordre de convergence optimal. Cette fonction spline peut etre interpretee comme une fonction spline cardinale tronquee avec une correction convenable. La technique utilisee pour les fonctions splines polynomiales est applicable dans le cas des fonctions splines sous tension. On donne aussi quelques resultats pour les fonctions splines cubiques de lissage

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Burton, Christina Marie. "Quadratic Spline Approximation of the Newsvendor Problem Optimal Cost Function." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/3087.

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We consider a single-product dynamic inventory problem where the demand distributions in each period are known and independent but with density. We assume the lead time and the fixed cost for ordering are zero and that there are no capacity constraints. There is a holding cost and a backorder cost for unfulfilled demand, which is backlogged until it is filled by another order. The problem may be nonstationary, and in fact our approximation of the optimal cost function using splines is most advantageous when demand falls suddenly. In this case the myopic policy, which is most often used in practice to calculate optimal inventory level, would be very costly. Our algorithm uses quadratic splines to approximate the optimal cost function for this dynamic inventory problem and calculates the optimal inventory level and optimal cost.

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Kim, Heeyoung. "Statistical methods for function estimation and classification." Diss., Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/44806.

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This thesis consists of three chapters. The first chapter focuses on adaptive smoothing splines for fitting functions with varying roughness. In the first part of the first chapter, we study an asymptotically optimal procedure to choose the value of a discretized version of the variable smoothing parameter in adaptive smoothing splines. With the choice given by the multivariate version of the generalized cross validation, the resulting adaptive smoothing spline estimator is shown to be consistent and asymptotically optimal under some general conditions. In the second part, we derive the asymptotically optimal local penalty function, which is subsequently used for the derivation of the locally optimal smoothing spline estimator. In the second chapter, we propose a Lipschitz regularity based statistical model, and apply it to coordinate measuring machine (CMM) data to estimate the form error of a manufactured product and to determine the optimal sampling positions of CMM measurements. Our proposed wavelet-based model takes advantage of the fact that the Lipschitz regularity holds for the CMM data. The third chapter focuses on the classification of functional data which are known to be well separable within a particular interval. We propose an interval based classifier. We first estimate a baseline of each class via convex optimization, and then identify an optimal interval that maximizes the difference among the baselines. Our interval based classifier is constructed based on the identified optimal interval. The derived classifier can be implemented via a low-order-of-complexity algorithm.

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5

Wu, Yuan. "The partially monotone tensor spline estimation of joint distribution function with bivariate current status data." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/762.

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The analysis of joint distribution function with bivariate event time data is a challenging problem both theoretically and numerically. This thesis develops a tensor splinebased nonparametric maximum likelihood estimation method to estimate the joint distribution function with bivariate current status data. The tensor I-splines are developed to replace the traditional tensor B-splines in approximating joint distribution function in order to simplify the restricted maximum likelihood estimation problem in computing. The generalized gradient projection algorithm is used to compute the restricted optimization problem. We show that the proposed tensor spline-based nonparametric estimator is consistent and that the rate of convergence is obtained. Simulation studies with moderate sample sizes show that the finite-sample performance of the proposed estimator is generally satisfactory.

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Wilson, Brigham Bond. "Infinitesimal Perturbation Analysis for the Capacitated Finite-Horizon Multi-Period Multiproduct Newsvendor Problem." BYU ScholarsArchive, 2012. https://scholarsarchive.byu.edu/etd/2988.

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An optimal ordering scheme for the capacitated, finite-horizon, multi-period, multiproduct newsvendor problem was proposed by cite {shao06} using a hedging point policy. This solution requires the calculation of a central curve that divides the different ordering regions and a vector that defines the target inventory levels. The central curve is a nonlinear curve that determines the optimal order quantities as a function of the initial inventory levels. In this paper we propose a method for calculating this curve and vector using spline functions, infinitesimal perturbation analysis (IPA), and convex optimization. Using IPA the derivatives of the cost with respect to the variables that determine the spline function are efficiently calculated. A convex optimization algorithm is used to optimize the spline function, resulting in a optimal policy. We present the mathematical derivations and simulation results validating this solution.

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Gomes, José Clelto Barros. "Estimação não-parametrica para função de covariancia de processos gaussianos espaciais." [s.n.], 2009. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306507.

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Orientador: Ronaldo Dias
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matematica, Estatistica e Computação Cientifica
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Resumo: O desafio na modelagem de processos espaciais está na descrição da estrutura de covariância do fenômeno sob estudo. Um estimador não-paramétrico da função de covariância foi construído de forma a usar combinações lineares de funções B-splines. Estas bases são usadas com muita frequência na literatura graças ao seu suporte compacto e a computação tão rápida quanto a habilidade de criar aproximações suaves e apropriadas. Verificouse que a função de covariância estimada era definida positiva por meio do teorema de Bochner. Para a estimação da função de covariância foi implementado um algoritmo que fornece um procedimento completamente automático baseado no número de funções bases. Então foram realizados estudos numéricos que evidenciaram que assintoticamente o procedimento é consistente, enquanto que para pequenas amostras deve-se considerar as restrições das funções de covariância. As funções de covariâncias usadas na estimação foram as de exponencial potência, gaussiana, cúbica, esférica, quadrática racional, ondular e família de Matérn. Foram estimadas ainda covariâncias encaixadas. Simulações foram realizadas também a fim de verificar o comportamento da distribuição da afinidade. As estimativas apresentaram-se satisfatórias
Abstract: The challenge in modeling of spatials processes is in description of the framework of covariance of the phenomenon about study. The estimation of covariance functions was done using a nonparametric linear combinations of basis functions B-splines. These bases are used frequently in literature thanks to its compact support and fast computing as the ability to create smooth and appropriate approaches There was positive definiteness of the estimator proposed by the Bochner's theorem. For the estimation of the covariance functions was implemented an algorithm that provides a fully automated procedure based on the number of basis functions. Then numerical studies were performed that showed that the procedure is consistent assynthotically. While for small samples should consider the restrictions of the covariance functions, so the process of optimization was non-linear optimization with restrictions. The following covariance functions were used in estimating: powered exponential, Gaussian, cubic, spherical, rational quadratic and Matérn family. Nested covariance funtions still were estimated. Simulations were also performed to verify the behavior of affinity and affinity partial, which measures how good is the true function of the estimated function. Estimates showed satisfactory
Mestrado
Mestre em Estatística

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8

Ludwig, Guilherme Vieira Nunes. "Estimação não paramétrica da função de covariância para dados funcionais agregados." [s.n.], 2011. http://repositorio.unicamp.br/jspui/handle/REPOSIP/306198.

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Orientadores: Nancy Lopes Garcia, Ronaldo Dias
Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Matemática, Estatística e Computação Científica
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Resumo: O objetivo desta dissertação é desenvolver estimadores não paramétricos para a função de covariância de dados funcionais agregados, que consistem em combinações lineares de dados funcionais que não podem ser observados separadamente. Estes métodos devem ser capazes de produzir estimativas que separem a covariância típica de cada uma das subpopulações que geram os dados, e que sejam funções não negativas definidas. Sob estas restrições, foi definida uma classe de funções de covariância não estacionarias, à qual resultados da teoria de estimação de covariância de processos estacionários podem ser estendidos. Os métodos desenvolvidos foram ilustrados com a aplicação em dois problemas reais: a estimação do perfil de consumidores de energia elétrica, em função do tempo, e a estimação da transmitância de substâncias puras em espectroscopia de infravermelho, através da inspeção de misturas, em função do espectro da luz
Abstract: The goal of this dissertation is to develop nonparametric estimators for the covariance function of aggregated functional data, which consists into linear combinations of functional data that cannot be sampled separately. Such methods must be able to produce estimates that not only separate the typical covariance of the subpopulations composing the data, but also be nonnegative definite functions. Under these restrictions, a class of nonstationary covariance functions was proposed, to which stationary processes' covariance function estimation results can be readily extended. The developed methods were illustrated with an application to two real problems: the estimation of electric energy consumers' profiles, as a function of the time of the day, and the estimation of the transmittance of pure substances in infrared spectroscopy, while inspecting mixtures of them, as a function of light spectrum
Mestrado
Estatistica Não Parametrica
Mestre em Estatística

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9

Mo, Eirik. "Nonlinear stochastic dynamics and chaos by numerical path integration." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2008. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1786.

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The numerical path integration method for solving stochastic differential equations is extended to solve systems up to six spatial dimensions, angular variables, and highly nonlinear systems - including systems that results in discontinuities in the response probability density function of the system. Novel methods to stabilize the numerical method and increase computation speed are presented and discussed. This includes the use of the fast Fourier transform (FFT) and some new spline interpolation methods. Some sufficient criteria for the path integration theory to be applicable is also presented. The development of complex numerical code is made possible through automatic code generation by scripting. The resulting code is applied to chaotic dynamical systems by adding a Gaussian noise term to the deterministic equation. Various methods and approximations to compute the largest Lyapunov exponent of these systems are presented and illustrated, and the results are compared. Finally, it is shown that the location and size of the additive noise term affects the results, and it is shown that additive noise for specific systems could make a non-chaotic system chaotic, and a chaotic system non-chaotic.

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10

Chen, Tianlei. "Cure Rate Models with Nonparametric Form of Covariate Effects." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/52894.

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This thesis focuses on development of spline-based hazard estimation models for cure rate data. Such data can be found in survival studies with long term survivors. Consequently, the population consists of the susceptible and non-susceptible sub-populations with the latter termed as "cured". The modeling of both the cure probability and the hazard function of the susceptible sub-population is of practical interest. Here we propose two smoothing-splines based models falling respectively into the popular classes of two component mixture cure rate models and promotion time cure rate models. Under the framework of two component mixture cure rate model, Wang, Du and Liang (2012) have developed a nonparametric model where the covariate effects on both the cure probability and the hazard component are estimated by smoothing splines. Our first development falls under the same framework but estimates the hazard component based on the accelerated failure time model, instead of the proportional hazards model in Wang, Du and Liang (2012). Our new model has better interpretation in practice. The promotion time cure rate model, motivated from a simplified biological interpretation of cancer metastasis, was first proposed only a few decades ago. Nonetheless, it has quickly become a competitor to the mixture models. Our second development aims to provide a nonparametric alternative to the existing parametric or semiparametric promotion time models.
Ph. D.

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11

Su, Weiji. "Flexible Joint Hierarchical Gaussian Process Model for Longitudinal and Recurrent Event Data." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1595850414934069.

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12

Barbosa, Daniel. "Automated assessment of cardiac morphology and function : An integrated B-spline framework for real-time segmentation and tracking of the left ventricle." Thesis, Lyon, INSA, 2013. http://www.theses.fr/2013ISAL0111.

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L’objectif principal de cette thèse est le développement de techniques de segmentation et de suivi totalement automatisées du ventricule gauche (VG) en RT3DE. Du fait de la nature difficile et complexe des données RT3DE, l’application directe des algorithmes classiques de vision par ordinateur est le plus souvent impossible. Les solutions proposées ont donc été formalisées et implémentées de sorte à satisfaire les contraintes suivantes : elles doivent permettre une analyse complètement automatique (ou presque) et le temps de calcul nécessaire doit être faible afin de pouvoir fonctionner en temps réel pour une utilisation clinique optimale. Dans ce contexte, nous avons donc proposé un nouveau cadre ou les derniers développements en segmentation d’images par ensembles de niveaux peuvent être aisément intégrés, tout en évitant les temps de calcul importants associés à ce type d’algorithmes. La validation clinique de cette approche a été effectuée en deux temps. Tout d’abord, les performances des outils développés ont été évaluées dans un contexte global se focalisant sur l’utilisation en routine clinique. Dans un second temps, la précision de la position estimée du contour du ventricule gauche a été mesurée. Enfin, les méthodes proposées ont été intégrées dans une suite logicielle utilisée à des fins de recherche. Afin de permettre une utilisation quotidienne efficace, des solutions conviviales ont été proposées incluant notamment un outil interactif pour corriger la segmentation du VG
The fundamental goal of the present thesis was the development of automatic strategies for left ventricular (LV) segmentation and tracking in RT3DE data. Given the challenging nature of RT3DE data, classical computer vision algorithms often face complications when applied to ultrasound. Furthermore, the proposed solutions were formalized and built to respect the following requirements: they should allow (nearly) fully automatic analysis and their computational burden should be low, thus enabling real-time processing for optimal online clinical use. With this in mind, we have proposed a novel segmentation framework where the latest developments in level-set-based image segmentation algorithms could be straightforwardly integrated, while avoiding the heavy computational burden often associated with level-set algorithms. Furthermore, a strong validation component was included in order to assess the performance of the proposed algorithms in realistic scenarios comprising clinical data. First, the performance of the developed tools was evaluated from a global perspective, focusing on its use in clinical daily practice. Secondly, also the spatial accuracy of the estimated left ventricular boundaries was assessed. As a final step, we aimed at the integration of the developed methods in an in-house developed software suite used for research purposes. This included user-friendly solutions for efficient daily use, namely user interactive tools to adjust the segmented left ventricular boundaries

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Forsman, Daniel. "Bangenerering för industrirobot med 6 frihetsgrader." Thesis, Linköping University, Department of Electrical Engineering, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2376.

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This thesis studies path generation for industrial robots of six degrees of freedom. A path is defined by connection of simple geometrical objects like arcs and straight lines. About each point at which the objects connect, a region, henceforth called a zone, is defined in which deviation from the defined path is permitted. The zone allows the robot to follow the path at a constant speed, but the acceleration needed may vary.

Some means of calculating the zone path as to make the acceleration continuous will be presented. In joint space the path is described by the use of cubic splines. The transformation of the Cartesian path to paths in joint space will be examined. Discontinuities in the second order derivatives will appear between the splines.

A few examples of different zone path calculations will be presented where the resulting spline functions are compared with respect to their first and second order derivatives. An investigation of the number of spline functions needed when, given an upper limit of deviation, the transformation back to Cartesian coordinates is made.

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GIOLDASIS, Georgios. "Essays in nonparametric econometrics with applications to the economics of productivity and innovation." Doctoral thesis, Università degli studi di Ferrara, 2018. http://hdl.handle.net/11392/2488198.

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Il presente lavoro si propone di applicare metodi di avanguardia nella teoria econometrica ed, in quest’ottica di rivisitare una serie di questioni economiche relative ai temi della produttività, della tecnologia e dell’innovazione. Il primo capitolo della tesi si concentra sul contesto parametrico. La letteratura mainstream sull’econometria della produttività e sul cambiamento tecnologico (CT) assumono l’additività del CT, introducendo cosı la neutralità à la Hicks derivante dal CT all’interno del modello. In questa prospettiva, all’ interno del capitolo si stima una funzione di produzione a livello di azienda che permette di allontanarsi dalla ipotesi usuale di neutralità à la Hicks relativa al CT. In parallelo, il capitolo affronta il tema dell’ endogenita dell’innovazione la quale è considerata una misura della CT. Le specificazioni parametriche che consentono un cambiamento tecnico non Hicks-neutral sono derivate. Il capitolo presenta anche delle condizioni verificabili per approssimazioni parametriche comuni, in base alle quali vale la neutralità Hicks. Le specificazioni Cobb-Douglas sono stimate adottando i metodi IV per un effetto eterogeneo dell’innovazione sulla produttività. I risultati empirici rifiutano la neutralità à la Hicks rispetto alla presenza di progresso tecnico capital-saving. Il secondo capitolo è connesso ai temi espressi all’interno del primo in una pluralità di aspetti. Il tema della localizzazione del cambiamento tecnologico viene affrontata utilizzando la serie di dati sulle aziende del capitolo precedente. A tal proposito, al fine di riconsiderare il rapporto tra innovazione e produttività, sono impiegati i recenti progressi sulla regressione kernel strumentale generalizzata. Tale esercizio permette di evidenziare l’eventuale presenza degli effetti di localizzazione di una variabile di innovazione endogena e, grazie alla ”smoothing” delle variabili discrete, di tenere conto delle tecnologie completamente eterogenee tra i diversi settori. Tali questioni sono estremamente rilevanti sia da una prospettiva teorica sia in termini di policy implications, ma non possono essere affrontate con l’adozione di approcci parametrici comuni. Il capitolo affronta anche il tema delle prestazioni predittive degli stimatori non parametrici rispetto ad alcune alternative parametriche. I risultati i) indicano che lo stimatore non parametrico proposto produce risultati migliori di quelli parametrici e ii) evidenziano alcuni modelli rilevanti che possono essere rilevati solo utilizzando lo stimatore non parametrico. Il terzo capitolo riesamina la questione delle ricadute internazionali delle attività di ricerca e sviluppo utilizzando metodi non parametrici, e verifica la validità dei risultati principali forniti nella letteratura rispetto alla possibile esistenza di non linearità, effetti di soglia e di relazioni non additive. In quest’ottica, esso considera una stimasieve di un modello di dati panel di diffusione tecnologica tra i paesi, focalizzandosi in particolar modo sulla questione della dipendenza dell’errore sezione trasversale. L’approccio semiparametrico adottato è un’estensione del modello fattore parametrico da Pesaran (2006). Il confronto tra l’approccio parametrico e semiparametrico rivela una prestazione migliore di quest’ultimo. Dal punto di vista economico, i risultati mostrano nuove prove rispetto ai benefici dei programmi di ricerca e sviluppo nazionali ed esteri per i paesi. Infine, l’ultimo capitolo della tesi è una revisione della regressione kernel non parametrica. Seguendo, soprattutto, il lavoro di Li e Racine (2007), riassume le caratteristiche chiavi di ”least squares cross validation” e della regressione kernel usando approcci costanti locali, lineari locali o polinomi locali.
This thesis is concerned with applying frontier methods in econometric theory, to revisit relevant economic questions concerning productivity, technology and innovation. The focal point of this thesis is to try to employ econometric techniques that may allow us to depart from the usual assumptions of linearity or additivity of the model, as is usually found in economic literature. Therefore, a binding common ground of all the chapters of this thesis is relaxing these restrictive assumptions, in economic topics relevant to productivity and innovation, in micro and macro level. In this framework, recent advancements in nonparametric econometric theory allow relaxing such model restrictions. The first chapter estimates a production function at firm level that allows departing from the standard hypothesis of Hicks-neutral technical change. Simultaneously, it is coping with the endogeneity of innovation, the latter being considered a measure of TC. Parametric specifications that allow non-Hicks neutral technical change are derived. The chapter also presents testable conditions, for common parametric approximations, under which Hicks neutrality holds. Cobb-Douglas specifications are estimated adopting IV methods for heterogeneous effect of innovation on productivity. The empirical results reject Hicks neutrality towards the presence of a capital-saving TC. Finally, this chapter serves as a link with the nonparametric approaches developed in the following ones. In the second chapter, the issue of localization of technical change is addressed using the firm level dataset of the previous chapter. Recent advances on generalized kernel instrumental regression are exploited in order to revisit the relationship between innovation and productivity. This allows to highlight the possible presence of a localized effect of an endogenous innovation variable and, thanks to smoothing discrete variables, also to account for fully heterogeneous technologies across sectors. Such issues are extremely relevant from both a theoretical and a policy oriented perspective but cannot be addressed by adopting common parametric approaches. The issue of the predictive performances of this nonparametric estimator when compared to some parametric alternatives is also addressed. The results i) indicate that the proposed nonparametric estimator performs better than parametric ones and ii) reveal some relevant patterns that can only be detected using the nonparametric estimator. The third chapter revisits the issue of international R&D spillovers by using nonparametric methods, and tests the validity of the main results provided in the literature with respect to the possible existence of nonlinearities, threshold effects and non-additive relations. It considers a sieve estimation of a panel data model of technology diffusion among countries, paying attention to the issue of error cross sectional dependence. The adopted semiparametric approach is an extension of the parametric factor model by Pesaran (2006). The comparison between the parametric and the semiparametric approach reveals a better performance of the latter. From an economic viewpoint, the results show new evidence with respect to the benefits of countries from domestic and foreign R&D. Finally, the last chapter of the thesis is a review of the nonparametric kernel regression. Following, mainly, the work of Li and Racine (2007), it summarizes the key features of least squares cross validation and the kernel regression using local constant, local linear or local polynomial approaches. Moreover, the nonparametric IV kernel regression is presented, along with the relevant topics of ill-posed inverse problems and regularization methods. This chapter serves also as an informal “appendix” of the previous chapters, especially for the ones concerning kernel regression, because it provides useful insights of the underlying methodologies.

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Bezchlebová, Daniela. "Analýza funkčních dat a modelování specifické míry úmrtnosti a plodnosti." Master's thesis, Vysoká škola ekonomická v Praze, 2014. http://www.nusl.cz/ntk/nusl-193581.

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The aim of this thesis is to analyze two major indicators representing the processes of natural changes in population, which are not influenced by age structure -- age specific fertility rate and age specific mortality rate and to introduce functional data analysis, which has recently become increasingly applied in many scientific fields. The functional data analysis is introduced on the Czech demographic data set for more than last sixty years. The thesis briefly describes historical development of mortality and fertility and also describes selected methods of functional data analysis by using statistical program R. Functional data analysis provides a wide variety of graphics tools to explore the data which we called functional and help us to explore all typical and atypical features, identify outliers etc.

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Andriamaro, Miangaly Gaelle. "Vector refinable splines and subdivision." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/1747.

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Thesis (MSc (Mathematics))--Stellenbosch University, 2008.
In this thesis we study a standard example of refinable functions, that is, functions which can be reproduced by the integer shifts of their own dilations. Using the cardinal B-spline as an introductory example, we prove some of its properties, thereby building a basis for a later extension to the vector setting. Defining a subdivision scheme associated to the B-spline refinement mask, we then present the proof of a well-known convergence result. Subdivision is a powerful tool used in computer-aided geometric design (CAGD) for the generation of curves and surfaces. The basic step of a subdivision algorithm consists of starting with a given set of points, called the initial control points, and creating new points as a linear combination of the previous ones, thereby generating new control points. Under certain conditions, repeated applications of this procedure yields a continuous limit curve. One important goal of this thesis is to study a particular extension of scalar subdivision to matrix subdivision ...

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Benhida, Soufia. "De l'optimisation pour l'aide à la décision : applications au problème du voyageur de commerce probabiliste et à l'approximation de données." Thesis, Normandie, 2018. http://www.theses.fr/2018NORMIR27.

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La 1ere partie de ce travail traite l'optimisation des tournées sous forme d'un problème d'optimisation nommé Le problème de Voyageur de Commerce. Dans cette partie nous nous intéressons à faire une riche présentation du problème de Voyageur de Commerce, ses variantes, puis nous proposons une stratégie de génération de contrainte pour la résolution du TSP. Ensuite on traite sa version stochastique : le problème de Voyageur de commerce Probabiliste. Nous proposons une formulation mathématique du PTSP et nous présentons des résultats numériques obtenus par résolution exacte pour une série d'instances de petite taille. Dans la seconde partie, nous proposons une méthode d'approximation générale permettant d'approcher différents type de données, d'abord nous traitons l'approximation d'un signal de vent (cas simple, ID), ensuite l'approximation d'un champ de vecteurs avec prise en compte de la topographie qui constitue la principale contribution de cette partie
The first part of this work deals with route optimization in the form of an optimization problem named The Traveler's Business Problem. In this part we are interested to make a rich presentation of the problem of Traveler Commerce, its variants, then we propose a strategy of constraint generation for the resolution of the TSP. Then we treat its stochastic version : the probabilistic business traveler problem. We propose a mathematical formulation of the PTSP and we present numerical results obtained by exact resolution for a series of small instances. In the second part, we propose a method of general approximation to approximate different type of data, first we treat the approximation of a wind signal (simple case, 1D), then the approximation of a vector field taking into account the topography which is the main contribution of this part

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Zhang, Han. "Detecting Rare Haplotype-Environmental Interaction and Nonlinear Effects of Rare Haplotypes using Bayesian LASSO on Quantitative Traits." The Ohio State University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=osu149969433115895.

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Hadrich, Ben Arab Atizez. "Étude des fonctions B-splines pour la fusion d'images segmentées par approche bayésienne." Thesis, Littoral, 2015. http://www.theses.fr/2015DUNK0385/document.

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Dans cette thèse nous avons traité le problème de l'estimation non paramétrique des lois de probabilités. Dans un premier temps, nous avons supposé que la densité inconnue f a été approchée par un mélange de base B-spline quadratique. Puis, nous avons proposé un nouvel estimateur de la densité inconnue f basé sur les fonctions B-splines quadratiques, avec deux méthodes d'estimation. La première est base sur la méthode du maximum de vraisemblance et la deuxième est basée sur la méthode d'estimation Bayésienne MAP. Ensuite, nous avons généralisé notre étude d'estimation dans le cadre du mélange et nous avons proposé un nouvel estimateur du mélange de lois inconnues basé sur les deux méthodes d'estimation adaptées. Dans un deuxième temps, nous avons traité le problème de la segmentation statistique semi supervisée des images en se basant sur le modèle de Markov caché et les fonctions B-splines. Nous avons montré l'apport de l'hybridation du modèle de Markov caché et les fonctions B-splines en segmentation statistique bayésienne semi supervisée des images. Dans un troisième temps, nous avons présenté une approche de fusion basée sur la méthode de maximum de vraisemblance, à travers l'estimation non paramétrique des probabilités, pour chaque pixel de l'image. Nous avons ensuite appliqué cette approche sur des images multi-spectrales et multi-temporelles segmentées par notre algorithme non paramétrique et non supervisé
In this thesis we are treated the problem of nonparametric estimation probability distributions. At first, we assumed that the unknown density f was approximated by a basic mixture quadratic B-spline. Then, we proposed a new estimate of the unknown density function f based on quadratic B-splines, with two methods estimation. The first is based on the maximum likelihood method and the second is based on the Bayesian MAP estimation method. Then we have generalized our estimation study as part of the mixture and we have proposed a new estimator mixture of unknown distributions based on the adapted estimation of two methods. In a second time, we treated the problem of semi supervised statistical segmentation of images based on the hidden Markov model and the B-sline functions. We have shown the contribution of hybridization of the hidden Markov model and B-spline functions in unsupervised Bayesian statistical image segmentation. Thirdly, we presented a fusion approach based on the maximum likelihood method, through the nonparametric estimation of probabilities, for each pixel of the image. We then applied this approach to multi-spectral and multi-temporal images segmented by our nonparametric and unsupervised algorithm

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Chen, Chen. "Evaluating Time-varying Effect in Single-type and Multi-type Semi-parametric Recurrent Event Models." Diss., Virginia Tech, 2015. http://hdl.handle.net/10919/64371.

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This dissertation aims to develop statistical methodologies for estimating the effects of time-fixed and time-varying factors in recurrent events modeling context. The research is motivated by the traffic safety research question of evaluating the influence of crash on driving risk and driver behavior. The methodologies developed, however, are general and can be applied to other fields. Four alternative approaches based on various data settings are elaborated and applied to 100-Car Naturalistic Driving Study in the following Chapters. Chapter 1 provides a general introduction and background of each method, with a sketch of 100-Car Naturalistic Driving Study. In Chapter 2, I assessed the impact of crash on driving behavior by comparing the frequency of distraction events in per-defined windows. A count-based approach based on mixed-effect binomial regression models was used. In Chapter 3, I introduced intensity-based recurrent event models by treating number of Safety Critical Incidents and Near Crash over time as a counting process. Recurrent event models fit the natural generation scheme of the data in this study. Four semi-parametric models are explored: Andersen-Gill model, Andersen-Gill model with stratified baseline functions, frailty model, and frailty model with stratified baseline functions. I derived model estimation procedure and and conducted model comparison via simulation and application. The recurrent event models in Chapter 3 are all based on proportional assumption, where effects are constant. However, the change of effects over time is often of primary interest. In Chapter 4, I developed time-varying coefficient model using penalized B-spline function to approximate varying coefficients. Shared frailty terms was used to incorporate correlation within subjects. Inference and statistical test are also provided. Frailty representation was proposed to link time-varying coefficient model with regular frailty model. In Chapter 5, I further extended framework to accommodate multi-type recurrent events with time-varying coefficient. Two types of recurrent-event models were developed. These models incorporate correlation among intensity functions from different type of events by correlated frailty terms. Chapter 6 gives a general review on the contributions of this dissertation and discussion of future research directions.
Ph. D.

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Bonawitz, Elizabeth Ann. "A duality approach to spline approximation." Diss., Virginia Tech, 1994. http://hdl.handle.net/10919/37448.

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This dissertation discusses a new approach to spline approximation. A periodic spline approximation 𝑓_M,m,N(x) = Σ_k=1^Nα_kΦ_M,k(x) to a periodic function 𝑓(x) is determined by requiring < Φ_m,j, 𝑓 - 𝑓_M,m,N > = 0 for j = 1,...,N, where the Φ_L,k's are the unique periodic spline basis functions of order 𝐿. Error estimates, examples and some relationships to wavelets are given for the case M - m = 2μ. The case M - m = 2µ + 1 is briefly discussed but not completely explored.
Ph. D.

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22

Santos, André Duarte dos. "Implied probability density functions: Estimation using hypergeometric, spline and lognormal functions." Master's thesis, Instituto Superior de Economia e Gestão, 2011. http://hdl.handle.net/10400.5/3372.

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Master of Science in Finance
This thesis examines the stability and accuracy of three different methods to estimate Risk-Neutral Density functions (RNDs) using European options. These methods are the Double-Lognormal Function (DLN), the Smoothed Implied Volatility Smile (SML) and the Density Functional Based on Confluent Hypergeometric function (DFCH). These methodologies were used to obtain the RNDs from the option prices with the underlying USDBRL (price of US dollars in terms of Brazilian reals) for different maturities (1, 3 and 6 months), and then tested in order to analyze which method best fits a simulated "true" world as estimated through the Heston model (accuracy measure) and which model has a better performance in terms of stability. We observed that in the majority of the cases the SML outperformed the DLN and DFCH in capturing the "true" implied skewness. The DFCH and DLN methods were better than the SML model at estimating the "true" Kurtosis. However, due to the higher sensitivity of the skewness and kurtosis measures to the tails of the distribution (all the information outside the available strike prices is extrapolated and the probability masses outside this range can have ininite forms) we also compared the tested models using the root mean integrated squared error (RMISE) which is less sensitive to the tails of the distribution. We observed that using the RMISE criteria, the DFCH outperformed the other methods as a better estimator of the "true" RND. Besides testing which model best captured the "true" world's expectations, we an¬alyzed the historical summary statistics of the RNDs obtained from the FX options on the USDBRL for the period between June 2006 (before the start of the subprime crisis) and February 2010 (seven months before the Brazilian general election).

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Donovan, George C. "Fractal functions, splines, and wavelet." Diss., Georgia Institute of Technology, 1995. http://hdl.handle.net/1853/30411.

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Ostroumov, Ivan Victorovich. "Interpolation of magnetic field characteristics by spline functions." Thesis, ІV National Scientific Conference of young scientists and students «Problems and prospects of Aeronautics and Astronautics» 28 – 29 October 2015 y – Kyiv, 2015. – P. 5, 2015. http://er.nau.edu.ua/handle/NAU/26579.

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Global Earth’s Magnetic field is one of the most important things in planetary structure. Magnetic field is also one of the key elements for navigation purposes. Its parameters are extremely important for direction detection and other applications. Modern navigation devices and sensors grounded on magnetic field characteristics use magnetic field models which do not contain data about human based part of magnetic field. That is why the aim of this work is to describe methodology of local magnetic field parameters measurement through the use of typical users equipment. Usually magnetic field is characterized by intensity vector. Intensity vector “T” is the sum of the vectors strengths of several fields. Typically, the vector T is estimated from its projections, on the some Cartesian coordinate system (Tx, Ty, Tz components). In addition, two angles are important: declination(D) and inclination(I), which indicate position of intensity vector in space, horizontal TH and vertical Tz components of T.

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Hassan, Mosavverul Meir Amnon J. "Constructing cubic splines on the sphere." Auburn, Ala., 2009. http://hdl.handle.net/10415/1790.

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Enrique, Eduardo Horacio. "Mathematical models based on spline functions for industrial applications." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/NQ60534.pdf.

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Ng'andu, Alvert Namasamu. "Estimation of rotational degrees of freedom using spline functions." Thesis, University of Nottingham, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282786.

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Mawk, Russell Lynn. "A survey of applications of spline functions to statistics." [Johnson City, Tenn. : East Tennessee State University], 2001. http://etd-submit.etsu.edu/etd/theses/available/etd-0714101-104229/restricted/mawksr0809.pdf.

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Matchett, Kyle Brian. "Independent regulation and function of SEPT9 splice variants." Thesis, Queen's University Belfast, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.534622.

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Grove, Olya. "Heterogeneous Modeling of Medical Image Data Using B-Spline Functions." Scholar Commons, 2011. http://scholarcommons.usf.edu/etd/3130.

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Ongoing developments in the field of medical imaging modalities have pushed the frontiers of modern medicine and biomedical engineering, prompting the need for new applications to improve diagnosis, treatment and prevention of diseases. Biomedical data visualization and modeling rely predominately on manual processing and utilization of voxel and facet based homogeneous models. Biological structures are naturally heterogeneous and in order to accurately design and biomimic biological structures, properties such as chemical composition, size and shape of biological constituents need to be incorporated in the computational biological models. Our proposed approach involves generating a density point cloud based on the intensity variations in a medical image slice, to capture tissue density variations through point cloud densities. The density point cloud is ordered and approximated with a set of cross-sectional least-squares B-Spline curves, based on which a skinned B-Spline surface is generated. The aim of this method is to capture and accurately represent density variations within the medical image data with a lofted surface function. The fitted B-Spline surface is sampled at uniformly distributed parameters, and our preliminary results indicate that the bio-CAD model preserves the density variations of the original image based point cloud. The resultant surface can thus be visualized by mapping the density in the parametric domain into color in pixel domain. The B-Spline function produced from each image slice can be used for medical visualization and heterogeneous tissue modeling. The process can be repeated for each slice in the medical dataset to produce heterogeneous B-Spline volumes. The emphasis of this research is placed on accuracy and shape fidelity needed for medical operations.

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Xiang, Hong. "Cardinal interpolation by splines and refinable functions." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/nq39609.pdf.

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Waters, Timothy Paul. "Finite element model updating using frequency response functions." Thesis, University of Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294617.

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Abdelhameed, Taher. "Role of src splice variants in nerve terminal function." Thesis, University of Edinburgh, 2010. http://hdl.handle.net/1842/4485.

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Src is a 60 kDa tyrosine kinase that is expressed in most of animal tissues. Src has three splice variants, C-src, which is ubiquitously expressed, and N1- and N2-src, which are neuronal specific splice variants. The srcs are differentially spliced at their SH3 domains, therefore the hypothesis is that this splicing allows them to have different binding partners and perform different roles in neurons. The aim of this project is to identify new interactions for the three src splice variants in neurons and their possible functional roles. The SH3 domains, kinase active truncated proteins ( 80) and kinase dead mutant full length versions of the three splice variants of src were cloned from a rat brain cDNA library into bacterial expression vectors. GST-pull downs from nerve terminal lysates showed that different src splice variants had different binding partners. These partners were identified by mass spectrometry and confirmed by western blotting. C-src binding partners included dynamin, synapsin, and synaptojanin, while N2-src binding partners included synaptophysin, Munc18-1, and NSF. The interaction between N2-src and Munc 18-1 was characterized further; however a number of in vitro interaction assays and kinase assays showed that Munc 18-1 may not be a direct binding partner for N2-src or substrate. N1-src displayed a stimulation-dependent interaction with dynamin I. This was shown to be phosphorylation-dependent in contrast to C-src binding. The major phosphorylation sites on dynamin I, S774 and S778, were not involved in the regulation of N1-src binding. The binding site for N1-src on dynamin I was different to C-src, with extensive mutagenesis studies suggesting that the interaction site is at the tail of the dynamin I xa splice variant, which has an additional two phosphorylation sites.

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INCH, OSCAR FABRICIO ZULETA. "FINITE ELEMENTS WITH SPLINE FUNCTIONS APPLIED TO STRUCTURAL DYNAMICS AND INSTABILITY." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2008. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=12139@1.

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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO
COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR
No presente trabalho se estuda um elemento finito subparamétrico que aproxima o campo de deslocamentos com funções spline, implementando um programa que pode ser utilizado para calculo estático, dinâmico e de instabilidade de estruturas compostas de placas, vigas de paredes finas, vigas caixão e em geral em elementos alongados (pontes e perfis metálicos). O grau de liberdade de rotação perpendicular ao plano do elemento é introduzido na formulação para possibilitar uma análise tridimensional. Apresenta-se um método que serve como base para determinar a constante de rigidez correspondente. Nos exemplos apresentados avalia-se a precisão obtida utilizando pouco número de divisões longitudinais do continuo, vantagem que justifica o uso desses elementos em estudos de pré-projeto ou otimização de estruturas. Comparam-se os resultados com soluções teóricas ou resultados de outros programas estruturais, permitindo apreciar as possibilidades e limitações da modelagem usando elementos finitos com funções spline. As diferenças observadas, que surgem principalmente em placas espessas, são explicadas pela aproximação da deformação de cisalhamento encontrada na literatura para os elementos utilizados na comparação. Mostra-se também exemplos de instabilidade analisados em três dimensões que permitem considerar diferentes condições de apoio e discutir os resultados de fórmulas conhecidas.
The present work presents a subparametric finite element model with spline displacement functions, implemented for static, dynamic and instability analysis of folded plates, thin-walled beams, box girders, and elongated structures such as bridges and structural shapes. A drilling degree of freedom (rotation about an axis perpendicular to the plane of the element) is introduced in the formulation to allow for three-dimensional analysis. A method for determining the corresponding contribution to the stiffness matrix is presented. The examples presented evaluate the accuracy obtained using a small number of longitudinal subdivisions of the continuum, convenient in the case of analyses for preliminary design and optimization. The results obtained are compared to theoretical solutions or results of standard structural analysis programs, allowing for an appraisal of the advantages and limitations of modeling with use of spline functions. The differences in the results, observed specially in the case of thick plates, are explained by the approximations for the shear strain in the elements used for comparison. From the examples it is possible to comment results of threedimensional modeling of instability problems with different boundary conditions.

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Clark, Troy Arthur. "The Trefoil: An Analysis in Curve Minimization and Spline Theory." Case Western Reserve University School of Graduate Studies / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=case1596460534956624.

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Van, der Bijl Rinske. "Multivariate refinable functions with emphasis on box splines." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/2743.

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Thesis (MComm (Mathematics))--Stellenbosch University, 2008.
The general purpose of this thesis is the analysis of multivariate refinement equations, with focus on the bivariate case. Since box splines are the main prototype of such equations (just like the cardinal B-splines in the univariate case), we make them our primary subject of discussion throughout. The first two chapters are indeed about the origin and definition of box splines, and try to elaborate on them in sufficient detail so as to build on them in all subsequent chapters, while providing many examples and graphical illustrations to make precise every aspect regarding box splines that will be mentioned. Multivariate refinement equations are ones that take on the form (x) =Xi2Zn pi (Mx − i), (1) where is a real-valued function, called a refinable function, on Rn, p = {pi}i2Zn is a sequence of real numbers, called a refinement mask, and M is an n × n matrix with integer entries, called a dilation matrix. It is important to note that any such equation is thus simultaneously determined by all three of , p and M — and the thesis will try and explain what role each of these plays in a refinement equation. In Chapter 3 we discuss the definition of refinement equations in more detail and elaborate on box splines as our first examples of refinable functions, also showing that one can actually use them to create even more such functions. Also observing from Chapter iii iv 2 that box splines demand yet another parameter from us, namely an initial direction matrix D, we focus on the more general instances of these in Chapter 4, while keeping the dilation matrix M fixed. Chapter 5 then in turn deals with the matrix M and tries to generalize some of the results found in Chapter 3 accordingly, keeping the initial direction matrix fixed. Having dealt with the refinement equation itself, we subsequently focus our attention on the support of a (bivariate) refinable function — that is, the part of the xy-grid on which such a function “lives” — and that of a refinement mask, in Chapter 6, and obtain a few results that are in a sense introductory to our work in the next chapter. Next, we move on to discuss one area in which refinable functions are especially applicable, namely subdivision, which is analyzed in Chapter 7. After giving the basic definitions of subdivision and subdivision convergence, and investigating the “sum rules” in Section 7.1, we prove our main subdivision convergence result in Section 7.2. The chapter is concluded with some examples in Section 7.3. The thesis is concluded, in Chapter 8, with a number of remarks on what has been done and issues that are left for future research.

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37

Chen, Eva T. "Estimation of the term structure of interest rates via cubic exponential spline functions." The Ohio State University, 1987. http://rave.ohiolink.edu/etdc/view?acc_num=osu1279824799.

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38

Poltera, Carina M. "Numerical analysis of spline generated surface Laplacian for ellipsoidal head geometry." Virtual Press, 2007. http://liblink.bsu.edu/uhtbin/catkey/1371849.

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Electroencephalography (EEG) is a valuable tool for clinical and cognitive applications. EEG allows for measuring and imaging of scalp potentials emitted by brain activity and allows researchers to draw conclusions about underlying brain activity and function. However EEG is limited by poor spatial resolution due to various factors. One reason is the fact that EEG electrodes are separated from current sources in the brain by cerebrospinal fluid (CSF), the skull, and the scalp. Unfortunately the conductivities of these tissues are not yet well known which limits the spatial resolution of EEG.Based on prior research, spatial resolution of the EEG can be improved via use of various mathematical techniques that provide increased accuracy of the representation of scalp potentials. One such method is the surface Laplacian. It has been shown to be a direct approach to improving EEG spatial resolution. Yet this approach depends on a geometric head model and much work has been done on assuming the human head to be spherical.In this project, we will develop a mathematical model for ellipsoidal head geometry based on surface Laplacian calculations by Law [1]. The ellipsoidal head model is more realistic to the human head shape and can therefore improve accuracy of the EEG imaging calculations. We will construct a computational program that utilizes the ellipsoidal head geometry in hopes to provide a more accurate representation of data fits compared to the spherical head models. Also, we will demonstrate that the spline surface Laplacian calculations do indeed increase the spatial resolution thereby affording a greater impact to the clinical and cognitive study community involving EEG.
Department of Physics and Astronomy

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39

Hajargasht, Gholamreza. "Non- and semi-parametric stochastic frontiers : a penalised spline approach /." [St. Lucia, Qld.], 2005. http://www.library.uq.edu.au/pdfserve.php?image=thesisabs/absthe19533.pdf.

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40

Guilak, Farzin G. "A Spline Framework for Optimal Representation of Semiperiodic Signals." Thesis, Portland State University, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3722040.

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Semiperiodic signals possess an underlying periodicity, but their constituent spectral components include stochastic elements which make it impossible to analytically determine locations of the signal's critical points. Mathematically, a signal's critical points are those at which it is not differentiable or where its derivative is zero. In some domains they represent characteristic points, which are locations indicating important changes in the underlying process reflected by the signal.

For many applications in healthcare, knowledge of precise locations of these points provides key insight for analytic, diagnostic, and therapeutic purposes. For example, given an appropriate signal they might indicate the start or end of a breath, numerous electrophysiological states of the heart during the cardiac cycle, or the point in a stride at which the heel impacts the ground. The inherent variability of these signals, the presence of noise, and often, very low signal amplitudes, makes accurate estimation of these points challenging.

There has been much effort in automatically estimating characteristic point locations. Approaches include algorithms operating in the time domain, on various transformations of the data, and using different models of the signal. These methods apply a wide variety of techniques ranging from simple thresholds and search windows to sophisticated signal processing and pattern recognition algorithms. Existing approaches do not explicitly use prior knowledge of characteristic point locations in their estimation.

This dissertation first develops a framework for an efficient parametric representation of semiperiodic signals using splines. It then implements an instance of that framework to optimally estimate locations of characteristic points, incorporating prior knowledge from manual annotations on training data. Splines represent signals in a piecewise manner by applying an interpolant to constraint points on the signal known as knots. The framework allows choice of interpolant, objective function, knot initialization algorithm, and optimization algorithm. After initialization it iteratively modifies knot locations until the objective function is met.

For optimal estimation of characteristic points the framework relies on a Bayesian objective function, the a posteriori probability of knot locations given the observed signal. This objective function fuses prior knowledge, the observed signal, and its spline estimate. With a linear interpolant, knot locations after optimization serve as estimates of the signal's characteristic points.

This implementation was used to determine locations of 11 characteristic points on a prospective test set comprising 200 electrocardiograph (ECG) signals from 20 subjects. It achieved a mean error of -0.4 milliseconds, less than one quarter of a sample interval. A low bias is not sufficient, however, and the literature recognizes error variance to be the more important factor in assessing accuracy. Error variances are typically compared to the variance of manual annotations provided by reviewers. The algorithm was within two standard deviations for six of the characteristic points, and within one sample interval of this criterion for another four points.

The spline framework described here provides a complementary option to existing methods for parametric modeling of semiperiodic signals, and can be tailored to represent semiperiodic signals with high fidelity or to optimally estimate locations of their characteristic points.

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41

Hauli, D. E. "Spline functions and their application to analysis of interval data : Breastfeeding durations and closed birth intervals." Thesis, University of Southampton, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.375510.

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42

Falanga, Alessia. "Compensatory relationship between exonic splicing enhancer, splice site and protein function." Thesis, Open University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.579797.

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The process of pre-mRNA splicing involves the removal of intronic sequences from the pre-mRNA and it is directed by intronic cis acting elements know as the 5' and 3' splice sites that mark the boundaries of the exons. Over the two decades, however, it has become clear that exons encode for auxiliary splicing signals that either enhance or perturb their inclusion in the final mRNA product. It is possible that the evolution of mRNA sequences could be conditioned by the presence of these exonic cis-acting splicing regulatory elements and not mainly by the selection of optimal protein function. To explore this hypothesis, I have investigated how the need for ESE influences the gene evolution of a paralogous gene family, specifically the human Alkaline Phosphatases (ALPs). In this work, I have identified in correspondence to a weak 3'splice site, two ESE sequences in the placental ALP exon 4, and demonstrate that the ESE are necessary for the exon inclusion in the mRNA due to the weak 3 'splice sites. Furthermore, I show that they are absent in the corresponding exon of the non-tissue specific ALP transcript, specifically exon 5 that carries a strong 3' splice site. Most importantly, the localization of the ESEs correspond to an area that in the paralogous non-tissue specific ALP gene differs in amino , acid composition with respect, not only to the placental ALP where I mapped the ESEs but also to the other members of the family, where this area is well conserved. These amino acid changes may represent a possible evolutionary constraint on enzymatic activity, in keeping with this hypothesis, substituting the amino acids in the region of the ESE for those of the paralogous non-tissue specific ALP gene increases the enzymatic activity. Thus splicing-related constraints challenge the primacy of biochemical function in rates of protein evolution.

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Tate, Sharon Amber. "A role for Survivin splice variant heterodimerisation in regulating Survivin function." Thesis, University of Cambridge, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.614019.

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Cisternas, Felipe A. "The function of alternatively spliced isoforms of dystrophin." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape2/PQDD_0018/MQ49767.pdf.

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45

Al-Shaikh, Enas. "Longitudinal Regression Analysis Using Varying Coefficient Mixed Effect Model." University of Cincinnati / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1342543464.

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46

Caulfield-Browne, Mark. "The application of spline functions for kinematic motion design with particular reference to cam mechanisms." Thesis, University of Nottingham, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.239929.

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47

Björkman, Henrik. "Alternative Methods for Assessment of Split Renal Function." Doctoral thesis, Uppsala University, Department of Oncology, Radiology and Clinical Immunology, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-8513.

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Living kidney donation is a clinical situation with unique features in the sense that healthy individuals voluntarily expose themselves to certain risks and inconveniences. Therefore, eliminating as much of the associated discomfort as possible is crucial. The primary aim of this study was to evaluate whether it is possible to use the examination with computed tomography (CT), which is essential to the investigation, also for determining the ratio of the two kidneys’ function – the split renal function. If possible, an examination with gamma camera renography could be excluded from the work-up.

To investigate this possibility, 27 subjects who had underwent CT and renography as part of kidney donor investigation were studied retrospectively. The quantity of contrast material in each kidney was considered proportional to that kidney’s function, and measurement was made in each of the two available contrast phases. The results were compared to the results from renography. A similar analysis was conducted in 38 patients investigated for suspected renal artery stenosis with CT and renography, including a study of an automatized method for the acquisition of data from CT. For further scrutiny, a respiratory triggered dynamic contrast-enhanced magnetic resonance imaging (MRI) examination was investigated in 26 individuals. Results of split renal function were compared with renography and with CT in a subgroup. To study the possibility of facilitating the data analysis with CT, a formula for approximation of the contrast attenuation was studied in 64 subjects. An analysis of the significance of choice of contrast phase was also conducted in 43 subjects.

Unsatisfactory agreement with renography resulted from the CT analysis of previous donors, partly due to technical shortcomings. However, the technique was recognized to have a potential value. In the subsequent material, the settings were improved, with beneficial effects on the agreement. Respiratory-triggered MRI generated high quality examinations of renal uptake and excretion, with results harmonizing well with renography and CT. The approximation formula applied to CT resulted in higher accuracy for renal volume assessment than with the automatic method, and an acceptable agreement of the split renal function estimate.

From the presented results, a revision of the current donor investigation protocol is suggested. CT gives sufficient information to exclude renography as a routine examination. In cases of uncertainty, renography is recommended for secondary evaluation.

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Wibulwas, Auragan. "Functional applications of CD44-splice variant expression in rheumatoid arthritis." Thesis, University College London (University of London), 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.409026.

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Xu, Xing Jian. "Characterization of the functional properties of P2X7 receptor splice variants." Thesis, University of Cambridge, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.610293.

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Santos, Tyssia Nogueira Maciel dos. "AvaliaÃÃo genÃtica da curva de lactaÃÃo de cabras saanen utilizando modelos de regressÃo aleatÃria." Universidade Federal do CearÃ, 2014. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=13819.

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Abstract:

CoordenaÃÃo de AperfeÃoamento de Pessoal de NÃvel Superior
O objetivo deste estudo foi realizar uma avaliaÃÃo genÃtico-quantitativa da curva de lactaÃÃo atÃ 305 dias de cabras da raÃa Saanen, avaliando distintos modelos de regressÃo aleatÃria para o melhor ajuste das trajetÃrias fixa e aleatÃrias desta curva, e assim estimar as covariÃncias e parÃmetros genÃticos associados a este perÃodo. Foram utilizados 11.018 controles leiteiros de 950 lactaÃÃes de cabras pertencentes a rebanhos associados ao Programa de Melhoramento GenÃtico de Caprinos Leiteiros (CaprageneÂ). Os efeitos fixos utilizados nas anÃlises foram de grupo de contemporÃneos, sexo das crias, tipo de ordenha e manejo. Foram avaliados 18 modelos, com diferentes ordens, para verificar o melhor ajuste simultÃneo das regressÃes para as trajetÃrias fixa e aleatÃrias (efeitos genÃticos aditivos diretos, de ambiente permanente e residual). Para ajuste da regressÃo fixa, foram utilizados os polinÃmios ordinÃrios e os polinÃmios ortogonais de Legendre, de segunda ordem. Para as regressÃes aleatÃrias, foram utilizados os polinÃmios ordinÃrios, os polinÃmios ortogonais de Legendre e as funÃÃes b-spline, variando da segunda a quarta ordem. O modelo com os polinÃmios ortogonais de Legendre de segunda ordem para a parte fixa e as funÃÃes b-spline de quarta ordem para a parte aleatÃria foi o mais adequado para o ajuste dos dados analisados. Na trajetÃria fixa, este modelo estimou o pico de lactaÃÃo entre 52-61 dias, com valor mÃdio de 2,378 kg de leite/dia. A curva iniciou-se com uma produÃÃo mÃdia de 2,298 kg/dia, encerrando aos 305 dias com uma produÃÃo mÃdia de 0,758 kg/dia. As estimativas de herdabilidade variaram de 0,294 Â 0,135 a 0,794 Â 0,075. Maior variabilidade genÃtica foi estimada para os controles leiteiros intermediÃrios na trajetÃria da curva de lactaÃÃo, entre 79 e 180 dias, com maiores estimativas de herdabilidade. As correlaÃÃes genÃticas entre os controles variaram entre 0,551 Â 0,125 e 0,998 Â 0,001, como maiores valores para produÃÃes de leite em dias prÃximos e subsequentes, e tornando-se menores Ã medida que os controles se distanciavam. A variabilidade genÃtica estimada indica que Ã possÃvel modificar por seleÃÃo a curva de lactaÃÃo das cabras Saanen da populaÃÃo estudada. Esta seleÃÃo deve ser realizada entre 79 e 180 dias de lactaÃÃo, perÃodo posterior ao pico de lactaÃÃo, entretanto onde se observaram as maiores herdabilidades. A seleÃÃo neste ponto permitirÃ alteraÃÃes na curva como um todo, em funÃÃo das respostas genÃticas correlacionadas.
The aim of this study was to perform a genetic-quantitative evaluation of the lactation curve up to 305 days of Saanen goats, fitting different random regression models to the best fit on the fixed and random trajectories of this curve and thus estimate the (co) variances and genetic parameters associated to this period. 11,018test-day milk yieldof 950 goats belonging to herds supported by the Dairy Goats Breeding Program (CaprageneÂ) were used. The fixed effects used in the analysis were contemporary group, sex of offspring, type of milking and management. 18 models with different orderswere evaluated, to verify the simultaneous best fit of the regressions for the fixed and random trajectories (direct additive genetic, permanent environmental and residual effects). Ordinary orthogonal polynomials and Legendre polynomials, of second order were used to fit the fixed regression. Ordinary polynomials, orthogonal Legendre polynomials and B-spline functions, ranging from second to fourth order, were used for fit the random regressions. The model with orthogonal Legendre polynomials of second order to the fixed part and the b-spline function of fourth order for the random part was the most suitable for the fitting of the data analyzed. In fixed path, this model estimated peak lactation between 52-61 days, with an average of 2.378 kg of milk / day. The curve began with an average yield of 2.298 kg / day, ending 305 days with an average yield of 0.758 kg / day. Heritability estimates ranged from 0.294 Â 0.135 to 0.794 Â 0.075. Greater genetic variability was estimated for the intermediate test-day yields in the trajectory of the lactation curve, between 79 and 180 days, with higher heritability estimates. Genetic correlations among the test-day yields ranged from 0.551 Â 0.125 and 0.998 Â 0.001, with higher values between milk yield in the next and subsequent days, and becoming smaller as the distanceamong the test-day yield increase. The estimated genetic variability indicates that it is possible to modify the lactation curve of Saanen goats of the study population. The selection should be performed between 79 and 180 days of lactation, after the peak of lactation, however where the greatest heritabilities were observed period. The selection on this point will change the curve as a whole on the basis of correlated genetic responses.

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