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Tesi sul tema "Targeted Maximum Likelihood Estimation"

Autore: Grafiati

Pubblicato: 25 gennaio 2025

Ultima modifica: 31 luglio 2025

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1

Schnitzer, Mireille. "Targeted maximum likelihood estimation for longitudinal data." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=114242.

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Semiparametric efficient methods in causal inference have been developed to robustly and efficiently estimate causal parameters. As in general causal estimation, the methods rely on a set of mathematical assumptions that translate into requirements of causal knowledge and confounder identification. Targeted maximum likelihood estimation (TMLE) methodology has been developed as a potential improvement on efficient estimating equations, in that it shares the qualities of double robustness (unbiasedness under partial misspecification) and semiparametric efficiency, but can be constructed to provi

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2

Sarovar, Varada. "Targeted Maximum Likelihood Estimation for Evaluation of the Health Impacts of Air Pollution." Thesis, University of California, Berkeley, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10279902.

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<p> The adverse effects of air pollution on human life is of serious concern for today’s society. Two population groups that are especially vulnerable to air pollution are pregnant women and their growing fetuses, and the focus of this thesis is to study the effects of air pollution on these populations. In order to address the methodological limitations in prior research, we quantify the impact of air pollution on various adverse pregnancy outcomes, utilizing machine learning and novel causal inference methods. Specifically, we utilize two semi-parametric, double robust, asymptotically

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3

Khanafer, Sajida. "Sensory Integration During Goal Directed Reaches: The Effects of Manipulating Target Availability." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23422.

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When using visual and proprioceptive information to plan a reach, it has been proposed that the brain combines these cues to estimate the object and/or limb’s location. Specifically, according to the maximum-likelihood estimation (MLE) model, more reliable sensory inputs are assigned a greater weight (Ernst & Banks, 2002). In this research we examined if the brain is able to adjust which sensory cue it weights the most. Specifically, we asked if the brain changes how it weights sensory information when the availability of a visual cue is manipulated. Twenty-four healthy subjects reached to v

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4

Ruprecht, Jürg. "Maximum likelihood estimation of multipath channels /." [S.l.] : [s.n.], 1989. http://e-collection.ethbib.ethz.ch/show?type=diss&nr=8789.

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5

Horbelt, Werner. "Maximum likelihood estimation in dynamical systems." [S.l. : s.n.], 2001. http://deposit.ddb.de/cgi-bin/dokserv?idn=963810812.

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6

Sabbagh, Yvonne. "Maximum Likelihood Estimation of Hammerstein Models." Thesis, Linköping University, Department of Electrical Engineering, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2061.

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<p>In this Master's thesis, Maximum Likelihood-based parametric identification methods for discrete-time SISO Hammerstein models from perturbed observations on both input and output, are investigated. </p><p>Hammerstein models, consisting of a static nonlinear block followed by a dynamic linear one, are widely applied to modeling nonlinear dynamic systems, i.e., dynamic systems having nonlinearity at its input. </p><p>Two identification methods are proposed. The first one assumes a Hammerstein model where the input signal is noise-free and the output signal is perturbed with colored noise. The

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7

Leeuw, Johannes Leonardus van der. "Maximum likelihood estimation of exact ARMA models /." Tilburg : Tilburg University Press, 1997. http://www.gbv.de/dms/goettingen/265169976.pdf.

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8

Ehlers, Rene. "Maximum likelihood estimation procedures for categorical data." Pretoria : [s.n.], 2002. http://upetd.up.ac.za/thesis/available/etd-07222005-124541.

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9

Zou, Yiqun. "Attainment of Global Convergence in Maximum Likelihood Estimation." Thesis, University of Manchester, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.511845.

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10

Mariano, Machado Robson José. "Penalised maximum likelihood estimation for multi-state models." Thesis, University College London (University of London), 2018. http://discovery.ucl.ac.uk/10060352/.

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Multi-state models can be used to analyse processes where change of status over time is of interest. In medical research, processes are commonly defined by a set of living states and a dead state. Transition times between living states are often interval censored. In this case, models are usually formulated in a Markov processes framework. The likelihood function is then constructed using transition probabilities. Models are specified using proportional hazards for the effect of covariates on transition intensities. Time-dependency is usually defined by parametric models, which can represent a

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11

Weng, Yu. "Maximum Likelihood Estimation of Logistic Sinusoidal Regression Models." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407796/.

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We consider the problem of maximum likelihood estimation of logistic sinusoidal regression models and develop some asymptotic theory including the consistency and joint rates of convergence for the maximum likelihood estimators. The key techniques build upon a synthesis of the results of Walker and Song and Li for the widely studied sinusoidal regression model and on making a connection to a result of Radchenko. Monte Carlo simulations are also presented to demonstrate the finite-sample performance of the estimators

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12

DeGroot, Don Johan. "Maximum likelihood estimation of spatially correlated soil properties." Thesis, Massachusetts Institute of Technology, 1985. http://hdl.handle.net/1721.1/15282.

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Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Civil Engineering, 1985.<br>MICROFICHE COPY AVAILABLE IN ARCHIVES AND ENGINEERING.<br>Bibliography: leaves 109-110.<br>by Don Johan DeGroot.<br>M.S.

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13

John, Andrea. "Maximum likelihood estimation in mis-specified reliability distributions." Thesis, Swansea University, 2003. https://cronfa.swan.ac.uk/Record/cronfa42494.

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This thesis examines some effects of fitting the wrong distribution to reliability data. The parametric analysis of any data usually assumes that the form of the underlying distribution is known. In practice, however, the choice of distribution is subject to error, so the analysis could involve estimating parameters from a mis-specified model. In this thesis, we consider theoretical and practical aspects of maximum likelihood estimation under such mis-specification. Due to its popularity and wide use, we take the Weibull distribution to be the mis-specified model, and look at the effects of fi

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14

White, Scott Ian. "Stochastic volatility: Maximum likelihood estimation and specification testing." Thesis, Queensland University of Technology, 2006. https://eprints.qut.edu.au/16220/1/Scott_White_Thesis.pdf.

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Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financial asset returns. While SV models have a number of theoretical advantages over competing variance modelling procedures they are notoriously difficult to estimate. The distinguishing feature of the SV estimation literature is that those algorithms that provide accurate parameter estimates are conceptually demanding and require a significant amount of computational resources to implement. Furthermore, although a significant number of distinct SV specifications exist, little attention has been pai

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15

White, Scott Ian. "Stochastic volatility : maximum likelihood estimation and specification testing." Queensland University of Technology, 2006. http://eprints.qut.edu.au/16220/.

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Stochastic volatility (SV) models provide a means of tracking and forecasting the variance of financial asset returns. While SV models have a number of theoretical advantages over competing variance modelling procedures they are notoriously difficult to estimate. The distinguishing feature of the SV estimation literature is that those algorithms that provide accurate parameter estimates are conceptually demanding and require a significant amount of computational resources to implement. Furthermore, although a significant number of distinct SV specifications exist, little attention has been pai

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16

Zaeva, Maria. "Maximum likelihood estimators for circular structural model." Birmingham, Ala. : University of Alabama at Birmingham, 2009. https://www.mhsl.uab.edu/dt/2009m/zaeva.pdf.

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Thesis (M.S.)--University of Alabama at Birmingham, 2009.<br>Title from PDF title page (viewed Jan. 21, 2010). Additional advisors: Yulia Karpeshina, Ian Knowles, Rudi Weikard. Includes bibliographical references (p. 19).

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17

Cule, Madeleine. "Maximum likelihood estimation of a multivariate log-concave density." Thesis, University of Cambridge, 2010. https://www.repository.cam.ac.uk/handle/1810/237061.

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Density estimation is a fundamental statistical problem. Many methods are eithersensitive to model misspecification (parametric models) or difficult to calibrate, especiallyfor multivariate data (nonparametric smoothing methods). We propose an alternativeapproach using maximum likelihood under a qualitative assumption on the shape ofthe density, specifically log-concavity. The class of log-concave densities includes manycommon parametric families and has desirable properties. For univariate data, theseestimators are relatively well understood, and are gaining in popularity in theory andpractic

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18

Hartford, Alan Hughes. "Computational approaches for maximum likelihood estimation for nonlinearmixed models." NCSU, 2000. http://www.lib.ncsu.edu/theses/available/etd-20000719-081254.

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<p><P>The nonlinear mixed model is an important tool for analyzingpharmacokinetic and other repeated-measures data.In particular, these models are used when the measured response for anindividual,,has a nonlinear relationship with unknown, random, individual-specificparameters,.Ideally, the method of maximum likelihood is used to find estimates forthe parameters ofthe model after integrating out the random effects in the conditionallikelihood. However, closed form solutions tothe integral are generally not available. As a result, methods have beenpreviously developed to find approximatemaximum

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19

Storer, Robert Hedley. "Adaptive estimation by maximum likelihood fitting of Johnson distributions." Diss., Georgia Institute of Technology, 1987. http://hdl.handle.net/1853/24082.

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20

Wang, Qiang. "Maximum likelihood estimation of phylogenetic tree with evolutionary parameters." Connect to this title online, 2004. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1083177084.

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Thesis (Ph. D.)--Ohio State University, 2004.<br>Title from first page of PDF file. Document formatted into pages; contains xi, 167 p.; also includes graphics Includes bibliographical references (p. 157-167). Available online via OhioLINK's ETD Center

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21

Fischer, Mareike. "Novel Mathematical Aspects of Phylogenetic Estimation." Thesis, University of Canterbury. Mathematics and Statistics, 2009. http://hdl.handle.net/10092/2331.

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In evolutionary biology, genetic sequences carry with them a trace of the underlying tree that describes their evolution from a common ancestral sequence. Inferring this underlying tree is challenging. We investigate some curious cases in which different methods like Maximum Parsimony, Maximum Likelihood and distance-based methods lead to different trees. Moreover, we state that in some cases, ancestral sequences can be more reliably reconstructed when some of the leaves of the tree are ignored - even if these leaves are close to the root. While all these findings show problems inherent to eit

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22

Duong, Chi-Hong. "Approches statistiques en pharmacoépidémiologie pour la prise en compte des facteurs de confusion indirectement mesurés dans les bases de données médico-administratives : Application aux médicaments pris au cours de la grossesse." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASR028.

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Les bases de données médico-administratives sont de plus en plus utilisées en pharmacoépidémiologie. Néanmoins, l'existence de facteurs de confusion (FDC) non mesurés et non pris en compte peut biaiser les analyses. Dans ce travail, nous explorons l'intérêt d'exploiter la richesse des données avec la sélection à large échelle d'un grand nombre de covariables mesurées corrélées avec d'éventuels facteurs manquants pour les ajuster indirectement. Ce concept est à la base du score de propension en grande dimension (hdPS), et nous appliquons la même démarche à la G-computation (GC) et l'estimation

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23

Boscarino, Andrea. "Deep Learning Models with Stochastic Targets: an Application for Transprecision Computing." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20078/.

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Il presente elaborato di tesi è parte di un ampio progetto finanziato dall’Unione Europea, sotto il programma Horizon 2020 per la ricerca e l’innovazione, Open Transprecision Computing (OPRECOMP). Il progetto, della durata di 4 anni, punta a superare l’assunto conservativo secondo cui ogni calcolo compiuto da sistemi e applicazioni computazionali debba essere eseguito utilizzando la massima precisione numerica. Tale assunto è finora risultato sensato in vista di un’efficienza computazionale sempre migliore col passare del tempo, secondo la legge di Moore. Com’è noto, nell’era attuale tale legg

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24

Xue, Huitian, and 薛惠天. "Maximum likelihood estimation of parameters with constraints in normaland multinomial distributions." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B47850012.

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Motivated by problems in medicine, biology, engineering and economics, con- strained parameter problems arise in a wide variety of applications. Among them the application to the dose-response of a certain drug in development has attracted much interest. To investigate such a relationship, we often need to conduct a dose- response experiment with multiple groups associated with multiple dose levels of the drug. The dose-response relationship can be modeled by a shape-restricted normal regression. We develop an iterative two-step ascent algorithm to estimate normal means and variances s

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25

Leroux, Brian. "Maximum likelihood estimation for mixture distributions and hidden Markov models." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/29176.

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This thesis deals with computational and theoretical aspects of maximum likelihood estimation for data from a mixture model and a hidden Markov model. A maximum penalized likelihood method is proposed for estimating the number of components in a mixture distribution. This method produces a consistent estimator of the unknown mixing distribution, in the sense of weak convergence of distribution functions. The proof of this result consists of establishing consistency results concerning maximum likelihood estimators (which have unrestricted number of components) and constrained maximum likelihoo

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26

Strasser, Helmut. "The covariance structure of conditional maximum likelihood estimates." Oldenbourg Verlag, 2012. http://epub.wu.ac.at/3619/1/covariance_final.pdf.

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In this paper we consider conditional maximum likelihood (cml) estimates for item parameters in the Rasch model under random subject parameters. We give a simple approximation for the asymptotic covariance matrix of the cml-estimates. The approximation is stated as a limit theorem when the number of item parameters goes to infinity. The results contain precise mathematical information on the order of approximation. The results enable the analysis of the covariance structure of cml-estimates when the number of items is large. Let us give a rough picture. The covariance matrix has a domi

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27

Gandhi, Mital A. "Robust Kalman Filters Using Generalized Maximum Likelihood-Type Estimators." Diss., Virginia Tech, 2009. http://hdl.handle.net/10919/29902.

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Estimation methods such as the Kalman filter identify best state estimates based on certain optimality criteria using a model of the system and the observations. A common assumption underlying the estimation is that the noise is Gaussian. In practical systems though, one quite frequently encounters thick-tailed, non-Gaussian noise. Statistically, contamination by this type of noise can be seen as inducing outliers among the data and leads to significant degradation in the KF. While many nonlinear methods to cope with non-Gaussian noise exist, a filter that is robust in the presence of outliers

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28

Kim, Hyunjung. "Unit Root Tests in Panel Data: Weighted Symmetric Estimation and Maximum Likelihood Estimation." NCSU, 2001. http://www.lib.ncsu.edu/theses/available/etd-20010823-091533.

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<p>There has been much interest in testing nonstationarity of panel data in the econometric literature. In the last decade, several tests based on the ordinary least squares and Lagrange multiplier methodhave been developed. In contrast to a unit root test in the univariate case,test statistics in panel data have Gaussian limiting distributions.This dissertation considers weighted symmetric estimation and maximum likelihood estimation in the autoregressive model with individual effects.The asymptotic distributions have been derived as the number of individuals and time periods become large. Th

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29

Hu, Huilin. "Large sample theory for pseudo-maximum likelihood estimates in semiparametric models /." Thesis, Connect to this title online; UW restricted, 1998. http://hdl.handle.net/1773/8936.

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30

Cheng, Yang. "Maximum likelihood estimation and computation in a random effect factor model." College Park, Md. : University of Maryland, 2004. http://hdl.handle.net/1903/1782.

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Thesis (Ph. D.) -- University of Maryland, College Park, 2004.<br>Thesis research directed by: Mathematics. Title from t.p. of PDF. Includes bibliographical references. Published by UMI Dissertation Services, Ann Arbor, Mich. Also available in paper.

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31

Chotikakamthorn, Nopporn. "A pre-filtering maximum likelihood approach to multiple source direction estimation." Thesis, Imperial College London, 1996. http://hdl.handle.net/10044/1/8634.

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32

Yang, Jian. "Semiparametric maximum likelihood estimation of nonlinear regression models and GARCH models." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1998. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape15/PQDD_0007/NQ27861.pdf.

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33

Skeen, Matthew E. (Matthew Edward). "Maximum likelihood estimation of fractional Brownian motion and Markov noise parameters." Thesis, Massachusetts Institute of Technology, 1991. http://hdl.handle.net/1721.1/42527.

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34

Thornton, K. M. "The use of sample spacings in parameter estimation with applications." Thesis, Cardiff University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.238217.

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35

Gillan, Catherine C. "Using the piecewise exponential distribution to model the length of stay in a manpower planning system." Thesis, University of Ulster, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.338317.

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36

Yildirim, Sinan. "Maximum likelihood parameter estimation in time series models using sequential Monte Carlo." Thesis, University of Cambridge, 2013. https://www.repository.cam.ac.uk/handle/1810/244707.

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Abstract (sommario):

Time series models are used to characterise uncertainty in many real-world dynamical phenomena. A time series model typically contains a static variable, called parameter, which parametrizes the joint law of the random variables involved in the definition of the model. When a time series model is to be fitted to some sequentially observed data, it is essential to decide on the value of the parameter that describes the data best, a procedure generally called parameter estimation. This thesis comprises novel contributions to the methodology on parameter estimation in time series models. Our prim

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37

SOUZA, MARCIO ALBUQUERQUE DE. "MAXIMUM LIKELIHOOD ESTIMATION OF THE DIRECTION-OF-ARRIVAL OF PSK MODULATED CARRIERS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2004. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=5718@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Em sistemas de comunicações móveis, a modulação digital em fase (PSK)é amplamente utilizada em esquemas de transmissão em rádio-propagação. Trabalhos anteriores consideraram alguns métodos baseados no critério de máxima verossimilhança (MV) para estimação de direção-de-chegada de sinais genéricos que atingem um conjunto (array) de sensores. Esta tese propõe um novo estimador MV para a direção-de-chegada, desenvolvido especificamente para sistemas de comunicação PSK. Dois modelos de transmissão são concebidos para estimaçã

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38

Irineo, Joseph B. (Joseph Bernard) 1976. "An object-oriented, maximum-likelihood parameter estimation program for GARCH(p,q)." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80074.

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39

Schneider, Grant W. "Maximum Likelihood Estimation for Stochastic Differential Equations Using Sequential Kriging-Based Optimization." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1406912247.

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40

Wang, Steven Xiaogang. "Maximum weighted likelihood estimation." Thesis, 2001. http://hdl.handle.net/2429/13844.

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A maximum weighted likelihood method is proposed to combine all the relevant data from different sources to improve the quality of statistical inference especially when the sample sizes are moderate or small. The linear weighted likelihood estimator (WLE), is studied in depth. The weak consistency, strong consistency and the asymptotic normality of the WLE are proved. The asymptotic properties of the WLE using adaptive weights are also established. A procedure for adaptively choosing the weights by using cross-validation is proposed in the thesis. The analytical forms of the "adaptive w

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41

"Optimal recursive maximum likelihood estimation." Sloan School of Management, Massachusetts Institute of Technology], 1987. http://hdl.handle.net/1721.1/2987.

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42

Seo, Byungtae. "Doubly-smoothed maximum likelihood estimation." 2007. http://etda.libraries.psu.edu/theses/approved/WorldWideIndex/ETD-2129/index.html.

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Buot, Max. "Genetic algorithms and maximum likelihood estimation /." 2003. http://wwwlib.umi.com/dissertations/fullcit/3108787.

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Richardson, Alice. "Maximum likelihood estimation of variance components." Master's thesis, 1991. http://hdl.handle.net/1885/133923.

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In this thesis, the Maximum Likelihood and Restricted Maximum Likelihood methods of estimating variance components are investigated for the one-way model. Expressions for the estimators and their variances are obtained, and algorithms for finding the estimates are tested by means of a Monte Carlo study. The quantitative effects of non-normality on the variability of estimates are discussed. Finally, diagnostic tests for identifying outliers and non-normality are proposed, and illustrated with data concerning soybean plant growth.

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Vicente, David José Marques. "Distributed Algorithms for Target Localization in Wireless Sensor Networks Using Hybrid Measurements." Master's thesis, 2017. http://hdl.handle.net/10362/27875.

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This dissertation addresses the target localization problem in wireless sensor networks (WSNs). WSNs is now a widely applicable technology which can have numerous practical applications and offer the possibility to improve people’s lives. A required feature to many functions of a WSN, is the ability to indicate where the data reported by each sensor was measured. For this reason, locating each sensor node in a WSN is an essential issue that should be considered. In this dissertation, a performance analysis of two recently proposed distributed localization algorithms for cooperative 3-D wirel

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Mai, Anh Tien. "Revisiting optimization algorithms for maximum likelihood estimation." Thèse, 2012. http://hdl.handle.net/1866/9828.

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Parmi les méthodes d’estimation de paramètres de loi de probabilité en statistique, le maximum de vraisemblance est une des techniques les plus populaires, comme, sous des conditions l´egères, les estimateurs ainsi produits sont consistants et asymptotiquement efficaces. Les problèmes de maximum de vraisemblance peuvent être traités comme des problèmes de programmation non linéaires, éventuellement non convexe, pour lesquels deux grandes classes de méthodes de résolution sont les techniques de région de confiance et les méthodes de recherche linéaire. En outre, il est possible d’exploiter la s

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47

Ehlers, Rene. "Maximum likelihood estimation procedures for categorical data." Diss., 2003. http://hdl.handle.net/2263/26533.

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Please read the abstract in the section, 00front, of this document<br>Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2005.<br>Mathematics and Applied Mathematics<br>unrestricted

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LIU, RONG-XUAN, and 劉鎔瑄. "Adversarial Image Description without Maximum Likelihood Estimation." Thesis, 2018. http://ndltd.ncl.edu.tw/handle/c46qaj.

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碩士<br>國立中正大學<br>電機工程研究所<br>106<br>A fully visible belief network trained with maximum-likelihood is a typical strategy to learn a language model. However such an approach yields the exposure bias due to different behaviors at training and inference stage: To predict the next symbol, the model has provided with preceding information that is available at training stage but not at inference stage, when it could result in worse predictions along with accumulated errors and increased sentence length. On the contrary, we train another neural paradigm for the image description via an adversarial fash

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Choi, Ji Eun. "Stochastic Volatility Models and Simulated Maximum Likelihood Estimation." Thesis, 2011. http://hdl.handle.net/10012/6045.

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Financial time series studies indicate that the lognormal assumption for the return of an underlying security is often violated in practice. This is due to the presence of time-varying volatility in the return series. The most common departures are due to a fat left-tail of the return distribution, volatility clustering or persistence, and asymmetry of the volatility. To account for these characteristics of time-varying volatility, many volatility models have been proposed and studied in the financial time series literature. Two main conditional-variance model specifications are the autoregres

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Tsai, Wen-Chi, and 蔡紋琦. "Maximum Likelihood Estimation of a Monotone Regression Function." Thesis, 1994. http://ndltd.ncl.edu.tw/handle/26048287023325781218.

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