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Relevant bibliographies by topics / Approximate Bayesian Computation / Dissertations / Theses

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Dissertations / Theses on the topic 'Approximate Bayesian Computation'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 July 2025

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1

Ratmann, Oliver Rene. "Approximate Bayesian Computation under model uncertainty." Thesis, Imperial College London, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.520934.

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2

Webster, Mark Graham Moody. "Convergence properties of approximate Bayesian computation." Thesis, University of Leeds, 2016. http://etheses.whiterose.ac.uk/16197/.

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Approximate Bayesian Computation is a family of Monte Carlo methods used for likelihood-free Bayesian inference, where calculating the likelihood is intractable, but it is possible to generate simulated data, and calculate summary statistics. While these methods are easy to describe and implement, it is not trivial to optimise the mean square error of the resulting estimate. This thesis focuses on asymptotic results for the rate of convergence of ABC to the true posterior expectation as the expected computational cost increases. Firstly, we examine the asymptotic efficiency of the "basic" vers

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3

Ruli, Erlis. "Recent Advances in Approximate Bayesian Computation Methods." Doctoral thesis, Università degli studi di Padova, 2014. http://hdl.handle.net/11577/3423529.

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The Bayesian approach to statistical inference in fundamentally probabilistic. Exploiting the internal consistency of the probability framework, the posterior distribution extracts the relevant information in the data, and provides a complete and coherent summary of post data uncertainty. However, summarising the posterior distribution often requires the calculation of awkward multidimensional integrals. A further complication with the Bayesian approach arises when the likelihood functions is unavailable. In this respect, promising advances have been made by theory of Approximate Bayesian Comp

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4

Fan, Hang. "Estimation of Species Tree Using Approximate Bayesian Computation." The Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1281732679.

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5

Prangle, Dennis. "Summary statistics and sequential methods for approximate Bayesian computation." Thesis, Lancaster University, 2011. http://eprints.lancs.ac.uk/62703/.

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Many modern statistical applications involve inference for complex stochastic models, where it is easy to simulate from the models, but impossible to calculate likelihoods. Approximate Bayesian computation (ABC) is a method of inference for such models. It replaces calculation of the likelihood by a step which involves simulating artificial data for different parameter values, and comparing summary statistics of the simulated data to summary statistics of the observed data. This thesis looks at two related methodological issues for ABC. Firstly a method is proposed to construct appropriate sum

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6

Campos, Thiago Feitosa. "Aplicações do approximate Bayesian computation a controle de qualidade." Universidade de São Paulo, 2015. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-15102015-174147/.

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Neste trabalho apresentaremos dois problemas do contexto de controle estatístico da qualidade: monitoramento \"on-line\'\' de qualidade e environmental stress screening, analisados pela óptica bayesiana. Apresentaremos os problemas dos modelos bayesianos relativos a sua aplicação e, os reanalisamos com o auxílio do ABC o que nos fornece resultados de uma maneira mais rápida, e assim possibilita análises diferenciadas e a previsão novas observações.<br>In this work we will present two problems in the context of statistical quality control: on line quality monitoring and environmental stress scr

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7

McCloskey, Rosemary Martha. "Phylogenetic estimation of contact network parameters with approximate Bayesian computation." Thesis, University of British Columbia, 2016. http://hdl.handle.net/2429/58663.

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Models of the spread of disease in a population often make the simplifying assumption that the population is homogeneously mixed, or is divided into homogeneously mixed compartments. However, human populations have complex structures formed by social contacts, which can have a significant influence on the rate and pattern of epidemic spread. Contact networks capture this structure by explicitly representing each contact that could possibly lead to a transmission. Contact network models parameterize the structure of these networks, but estimating their parameters from contact data requires exte

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8

Simola, Umberto. "Developments in Approximate Bayesian Computation and Statistical Applications in Astrostatistics." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3423284.

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The title of this Thesis embraces two topics that have been investigated. Most of the present work is dedicated to develops and extensions for Approximate Bayesian Computation (ABC). While several algorithms have been proposed to improve the efficiency of the basic ABC algorithm, a number of subjective choices is left to the researcher. Several of these choices have not only an impact on the efficiency of the algorithm but also on its capability to approximate properly the true posterior distribution. We present a first extension of the ABC Population Monte-Carlo (ABC-PMC) algorithm aimed by t

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9

Junior, Ricardo Fernandes Campos. "Divergência populacional e expansão demográfica de Dendrocolaptes platyrostris (Aves: Dendrocolaptidae) no final do Quaternário." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/41/41131/tde-22012013-102652/.

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Dendrocolaptes platyrostris é uma espécie de ave florestal associada às matas de galeria do corredor de vegetação aberta da América do sul (D. p. intermedius) e à Floresta Atlântica (D. p. platyrostris). Em um trabalho anterior, foi observada estrutura genética populacional associada às subespécies, além de dois clados dentro da Floresta Atlântica e evidências de expansão na população do sul, o que é compatível com o modelo Carnaval-Moritz. Utilizando approximate Bayesian computation, o presente trabalho avaliou a diversidade genética de dois marcadores nucleares e um marcador mitocondrial des

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10

Bergqvist, Oscar. "Calibration of Breast Cancer Natural History Models Using Approximate Bayesian Computation." Thesis, KTH, Matematisk statistik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-273605.

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Natural history models for breast cancer describe the unobservable disease progression. These models can either be fitted using likelihood-based estimation to data on individual tumour characteristics, or calibrated to fit statistics at a population level. Likelihood-based inference using individual level data has the advantage of ensuring model parameter identifiability. However, the likelihood function can be computationally heavy to evaluate or even intractable. In this thesis likelihood-free estimation using Approximate Bayesian Computation (ABC) will be explored. The main objective is to

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11

Ghosh, Sanmitra. "Fast approximate Bayesian computation for inference in non-linear differential equations." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/405506/.

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Complex biological systems are often modelled using non-linear differential equations which provide a rich framework for describing the dynamic behaviour of many interacting physical variables representing quantities of biological importance. Approximate Bayesian computation (ABC) using a sequential Monte Carlo (SMC) algorithm is a Bayesian inference methodology that provides a comprehensive platform for parameter estimation, model selection and sensitivity analysis in such non-linear differential equations. However, this method incurs a significant computational cost as it requires explicit n

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12

An, Ziwen. "Contributions to Bayesian synthetic likelihood." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/204971/1/Ziwen_An_Thesis.pdf.

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Complex statistical models pose a great challenge to practitioners because of methodological and computational difficulties. While traditional ways of running statistical inference are prohibitive for various reasons, new methods which rely only on model simulations have received increasing attention. This thesis develops novel simulation-based statistical inference methods that are both computationally efficient and robust allowing them to perform well on a wide variety of applications. We also provide statistical software to facilitate timely analyses.

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13

Toni, Tina. "Approximate Bayesian computation for parameter inference and model selection in systems biology." Thesis, Imperial College London, 2010. http://hdl.handle.net/10044/1/11481.

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In this thesis we present a novel algorithm for parameter estimation and model selection of dynamical systems. The algorithm belongs to the class of approximate Bayesian computation (ABC) methods, which can evaluate posterior distributions without having to calculate likelihoods. It is based on a sequential Monte Carlo framework, which gives our method a computational advantage over other existing ABC methods. The algorithm is applied to a wide variety of biological systems such as prokaryotic and eukaryotic signalling and stress response pathways, gene regulatory networks, and infectious dise

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14

Goosen, Kelly. "Calibrating high frequency trading data to agent based models using approximate Bayesian computation." Master's thesis, Faculty of Science, 2021. http://hdl.handle.net/11427/33699.

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We consider Sequential Monte Carlo Approximate Bayesian Computation (SMC ABC) as a method of calibration for the use of agent based models in market micro-structure. To date, there are no successful calibrations of agent based models to high frequency trading data. Here we test whether a more sophisticated calibration technique, SMC ABC, will achieve this feat on one of the leading agent based models in high frequency trading literature (the Preis-Golke-Paul-Schneider Agent Based Model (Preis et al., 2006)). We find that, although SMC ABC's naive approach of updating distributions can successf

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15

Langenfeld, Natalie Rose. "A novel sequential ABC algorithm with applications to the opioid crisis using compartmental models." Diss., University of Iowa, 2018. https://ir.uiowa.edu/etd/6171.

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The abuse of and dependence on opioids are major public health problems, and have been the focus of intense media coverage and scholarly inquiry. This research explores the problem in Iowa through the lens of infectious disease modeling. We wanted to identify the current state of the crisis, factors affecting the progression of the addiction process, and evaluate interventions as data becomes available. We introduced a novel sequential Approximate Bayesian Computation technique to address shortcomings of existing methods in this complex problem space, after surveying the literature for availab

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EMVALOMENOS, Gaelle. "Quantitative Methods For Detection of Transient Changes in Endogenous Dopamine For Preclinical PET Studies." Thesis, The University of Sydney, 2021. https://hdl.handle.net/2123/25710.

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This thesis investigates quantitative methods for the characterisation of dopamine (DA) release in preclinical PET. The goal was to develop methodologies that improve quantification of the PET signal and test to what extent these techniques can reliably detect subtle DA fluctuations. Ultimately, reliable quantification could help to better understand the role of DA in human brain conditions. The focus of this work is kinetic modelling, whose accuracy depends on different factors, from the quality of the measured imaging data to the interpretation of parameter estimates. An investigation of th

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17

Turner, Brandon Michael. "Likelihood-Free Bayesian Modeling." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1316714657.

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18

Daly, Aidan C. "Statistical tools and community resources for developing trusted models in biology and chemistry." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:4e936e3b-7985-44f0-814c-7be3433bdcbb.

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Mathematical modeling has been instrumental to the development of natural sciences over the last half-century. Through iterated interactions between modeling and real-world exper- imentation, these models have furthered our understanding of the processes in biology and chemistry that they seek to represent. In certain application domains, such as the field of car- diac biology, communities of modelers with common interests have emerged, leading to the development of many models that attempt to explain the same or similar phenomena. As these communities have developed, however, reporting standa

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Duchén, Bocángel Pablo. "Modeling the demographic history of Drosophila melanogaster using Approximate Bayesian Computation and Next Generation Sequencing Data." Diss., Ludwig-Maximilians-Universität München, 2013. http://nbn-resolving.de/urn:nbn:de:bvb:19-164700.

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The main goal of this thesis was to develop demographic models of the fruit fly Drosophila melanogaster using Approximate Bayesian Computation and Next Generation Sequencing Data. These models were used to reconstruct the history of African, European, and North American populations. Chapter 1 deals with the demographic history of North American D. melanogaster. This project was motivated by the release of full-genome sequences of a North American population, which showed greater diversity than European D. melanogaster although the introduction of the fruit fly to North America dates back to

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20

Carr, Michael John. "Estimating parameters of a stochastic cell invasion model with Fluorescent cell cycle labelling using approximate Bayesian computation." Thesis, Queensland University of Technology, 2021. https://eprints.qut.edu.au/226946/1/Michael_Carr_Thesis.pdf.

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Understanding the underlying mechanisms of melanoma cell behaviour is crucial to developing better drug treatment methods. In this thesis, we use advanced mathematical modelling and statistical inference techniques to obtain, for the first time, accurate estimates of the rates at which cells multiply and spread at multiple stages of the cell cycle. The mathematical model is fitted to data that uses fluorescent cell cycle labelling technology to visualise different phases of the cell cycle in real time. The accurately calibrated mathematical model enables a deeper understanding of cell behaviou

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21

Kelly, Ryan P. "Implementing Bayesian synthetic likelihood within the engine for likelihood-free inference." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/233759/1/Ryan_Kelly_Thesis.pdf.

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Scientific fields increasingly need to analyse complex phenomenon where a statistical model is not available due to methodological or computational difficulties. In this thesis, methods that instead rely on model simulations are contributed to the software package Engine for Likelihood-Free Inference. The implementation of these methods will assist practitioners across various domains to use advanced statistical methods to conduct inference on their data. Validation of the implemented methods was done on various simulated and real-world applications.

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22

Stocks, Michael. "Neutral and Adaptive Processes Shaping Genetic Variation in Spruce Species." Doctoral thesis, Uppsala universitet, Växtekologi och evolution, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-207714.

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Population genetic analyses can provide information about both neutral and selective evolutionary processes shaping genetic variation. In this thesis, extensive population genetic methods were used to make inferences about genetic drift and selection in spruce species. In paper I we studied four species from the Qinghai-Tibetan Plateau (QTP): Picea likiangensis, P. purpurea, P. wilsonii and P. schrenkiana. Big differences in estimates of genetic diversity and Ne were observed in the more restricted species, P. schrenkiana, and the other more widely distributed species. Furthermore, P. purpurea

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23

Priddle, Jacob William. "Efficient and flexible Bayesian synthetic likelihood via transformations." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/205902/1/Jacob_Priddle_Thesis.pdf.

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Simulator models are a type of stochastic model that is often used to approximate a real-life process. Current statistical methods for simulator models are computationally intensive, relying on a large number of model simulations. In this thesis, we develop new, efficient and flexible statistical methods that can be used for complex statistical models, such as simulator models. The new methods are theoretically justified and applied to a variety of simulated and real-life modelling scenarios from ecology and biology.

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24

Raynal, Louis. "Bayesian statistical inference for intractable likelihood models." Thesis, Montpellier, 2019. http://www.theses.fr/2019MONTS035/document.

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Dans un processus d’inférence statistique, lorsque le calcul de la fonction de vraisemblance associée aux données observées n’est pas possible, il est nécessaire de recourir à des approximations. C’est un cas que l’on rencontre très fréquemment dans certains champs d’application, notamment pour des modèles de génétique des populations. Face à cette difficulté, nous nous intéressons aux méthodes de calcul bayésien approché (ABC, Approximate Bayesian Computation) qui se basent uniquement sur la simulation de données, qui sont ensuite résumées et comparées aux données observées. Ces comparaisons

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Moores, Matthew T. "Bayesian computational methods for spatial analysis of images." Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/84728/12/84728%28thesis%29.pdf.

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This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

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Andrade, Plinio Lucas Dias. "Estimação do índice de memória em processos estocásticos com memória longa: uma abordagem via ABC." Universidade de São Paulo, 2016. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-03052016-183520/.

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Neste trabalho propomos o uso de um método Bayesiano para estimar o parâmetro de memória de um processo estocástico com memória longa quando sua função de verossimilhança é intratável ou não está disponível. Esta abordagem fornece uma aproximação para a distribuição a posteriori sobre a memória e outros parâmetros e é baseada numa aplicação simples do método conhecido como computação Bayesiana aproximada (ABC). Alguns estimadores populares para o parâmetro de memória serão revisados e comparados com esta abordagem. O emprego de nossa proposta viabiliza a solução de problemas complexos sob o po

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Dehideniya, Mahasen Bandara. "Optimal Bayesian experimental designs for complex models." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/131625/1/Dissanayake%20Mudiyanselage%20Mahasen_Dehideniya_Thesis.pdf.

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The complexity of statistical models that are used to describe biological processes poses significant computational challenges in design of experiments. To address such challenges, in this thesis, new methods are developed in optimisation and approximate inference, and are applied in real-world experiments. The proposed methods enable practitioners to gain greater insight and understanding into the biological processes they are studying, and this is demonstrated by designing experiments to understand important biological processes in epidemiology and ecology such as the spread of infectious di

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Lagarrigues, Guillaume. "Variabilité démographique et adaptation de la gestion aux changements climatiques en forêt de montagne : calibration par Calcul Bayésien Approché et projection avec le modèle Samsara2." Thesis, Université Grenoble Alpes (ComUE), 2016. http://www.theses.fr/2016GREAV081/document.

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Les hêtraies-sapinières-pessières de montagne paraissent particulièrement menacées par le réchauffement climatique. Pour appréhender la dynamique future de ces forêts et adapter la sylviculture à ces nouvelles conditions, il est important de mieux connaître les facteurs environnementaux impactant la démographie de ces espèces. Nous avons abordé cette problématique en combinant des données historiques de gestion, le modèle de dynamique forestière Samsara2 et une méthode de calibration basée sur le Calcul Bayésien Approché. Nous avons ainsi pu étudier conjointement les différents processus démog

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Li, Sen. "Inferring Evolutionary Processes of Humans." Doctoral thesis, Uppsala universitet, Evolutionsbiologi, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-183517.

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More and more human genomic data has become available in recent years by the improvement of DNA sequencing technologies. These data provide abundant genetic variation information which is an important resource to help us to understand the evolutionary history of humans. In this thesis I evaluated the performance of the Approximate Bayesian Computation (ABC) approach for inferring demographic parameters for large-scale population genomic data. According to simulation results, I can conclude that the ABC approach will continue to be a useful tool for analysing realistic genome-wide population-ge

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Duchén, Bocángel Pablo [Verfasser], and Wolfgang [Akademischer Betreuer] Stephan. "Modeling the demographic history of Drosophila melanogaster using Approximate Bayesian Computation and Next Generation Sequencing Data / Pablo Duchén Bocángel. Betreuer: Wolfgang Stephan." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2013. http://d-nb.info/1046503359/34.

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St, Onge Kate. "Demography and Polyploidy in Capsella." Doctoral thesis, Uppsala universitet, Evolutionär funktionsgenomik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-136696.

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Studies of demography and population structure give insight into important evolutionary processes such as speciation and diversification. In the present work I perform such studies in the genus Capsella, which has three species: C. grandiflora, an outcrossing diploid, C. rubella a selfing diploid, and C. bursa-pastoris a selfing tetraploid. These three species make a good model system for evolutionary studies because they encompass two major plant evolutionary processes: mating system shifts and polyploidization. To conduct my studies I have gathered a large number of samples across the distri

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Saulnier, Emma. "Phylodynamique des pathogènes viraux par calcul bayésien approché." Thesis, Montpellier, 2017. http://www.theses.fr/2017MONTT109.

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Inférer des paramètres épidémiologiques à partir de phylogénies ou de données d'incidence est toujours un enjeu.D'une part, les approches basées sur les données d'incidence donnent souvent des estimations erronées du fait du biais d'échantillonnage important sur ce type de données.D'autre part, les approches utilisant les phylogénies reposent généralement sur des fonctions de vraisemblance exprimées à partir de modèles démographiques relativement simples et peu pertinents au regard des dynamiques épidémiologiques.A notre connaissance, il n'existe aucune méthode d'inférence utilisant les deux t

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Warne, David James. "Computational inference in mathematical biology: Methodological developments and applications." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/202835/1/David_Warne_Thesis.pdf.

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Complexity in living organisms occurs on multiple spatial and temporal scales. The function of tissues depends on interactions of cells, and in turn, cell dynamics depends on intercellular and intracellular biochemical networks. A diverse range of mathematical modelling frameworks are applied in quantitative biology. Effective application of models in practice depends upon reliable statistical inference methods for experimental design, model calibration and model selection. In this thesis, new results are obtained for quantification of contact inhibition and cell motility mechanisms in prostat

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Wennerström, Lovisa. "Population genetic patterns in continuous environments in relation to conservation management." Doctoral thesis, Stockholms universitet, Zoologiska institutionen, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-131223.

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Genetic variation is a prerequisite for the viability and evolution of species. Information on population genetic patterns on spatial and temporal scales is therefore important for effective management and for protection of biodiversity. However, incorporation of genetics into management has been difficult, even though the need has been stressed for decades. In this thesis population genetic patterns in continuous environments are described, compared among species, and related to conservation management. The model systems are moose (Alces alces) in Sweden and multiple species in the Baltic Sea

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Lennon, Hannah. "Gaussian copula modelling for integer-valued time series." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/gaussian-copula-modelling-for-integervalued-time-series(fff45515-19a4-4063-8ad2-4f9aac4017cb).html.

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This thesis is concerned with the modelling of integer-valued time series. The data naturally occurs in various areas whenever a number of events are observed over time. The model considered in this study consists of a Gaussian copula with autoregressive-moving average (ARMA) dependence and discrete margins that can be specified, unspecified, with or without covariates. It can be interpreted as a 'digitised' ARMA model. An ARMA model is used for the latent process so that well-established methods in time series analysis can be used. Still the computation of the log-likelihood poses many proble

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Tavares, Gustavo Medina. "Resgatando a diversidade genética e história demográfica de povos nativos americanos através de populações mestiças do sul do Brasil e Uruguai." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2018. http://hdl.handle.net/10183/180568.

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Após a chegada dos conquistadores europeus, as populações nativas americanas foram dizimadas por diversas razões, como guerras e doenças, o que possivelmente levou diversas linhagens genéticas autóctones à extinção. Entretanto, durante essa invasão, houve miscigenação entre os colonizadores e os povos nativos e muitos estudos genéticos têm mostrado uma importante contribuição matrilinear nativa americana na formação da população colonial. Portanto, se muitos indivíduos na atual população urbana brasileira carregam linhagens nativas americanas no seu DNA mitocondrial (mtDNA), muito da diversida

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Ebert, Anthony C. "Dynamic queueing networks: Simulation, estimation and prediction." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/180771/1/Anthony_Ebert_Thesis.pdf.

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Inspired by the problem of managing passenger flow in airport terminals, novel statistical approaches to simulation, estimation and prediction of these systems were developed. A simulation algorithm was developed with computational speed-ups of more than one hundred-fold. The computational improvement was leveraged to infer parameters governing a dynamic queueing system for the first time. Motivated by the original application, contributions to both functional data analysis as well as combined parameter and state inference were made.

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Ibeh, Neke. "Inferring Viral Dynamics from Sequence Data." Thesis, Université d'Ottawa / University of Ottawa, 2016. http://hdl.handle.net/10393/35317.

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One of the primary objectives of infectious disease research is uncovering the direct link that exists between viral population dynamics and molecular evolution. For RNA viruses in particular, evolution occurs at such a rapid pace that epidemiological processes become ingrained into gene sequences. Conceptually, this link is easy to make: as RNA viruses spread throughout a population, they evolve with each new host infection. However, developing a quantitative understanding of this connection is difficult. Thus, the emerging discipline of phylodynamics is centered on reconciling epidemi

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Parat, Florence [Verfasser], Aurélien [Akademischer Betreuer] Tellier, Chris-Carolin [Gutachter] Schön, and Aurélien [Gutachter] Tellier. "Inference of the Demographic History of Domesticated Species Using Approximate Bayesian Computation and Likelihood-based Methods / Florence Parat ; Gutachter: Chris-Carolin Schön, Aurélien Tellier ; Betreuer: Aurélien Tellier." München : Universitätsbibliothek der TU München, 2020. http://d-nb.info/1213026083/34.

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Vo, Brenda. "Novel likelihood-free Bayesian parameter estimation methods for stochastic models of collective cell spreading." Thesis, Queensland University of Technology, 2016. https://eprints.qut.edu.au/99588/1/Brenda_Vo_Thesis.pdf.

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Biological processes underlying skin cancer growth and wound healing are governed by various collective cell spreading mechanisms. This thesis develops new statistical methods to provide key insights into the mechanisms driving the spread of cell populations such as motility, proliferation and cell-to-cell adhesion, using experimental data. The new methods allow us to precisely estimate the parameters of such mechanisms, quantify the associated uncertainty and investigate how these mechanisms are influenced by various factors. The thesis provides a useful tool to measure the efficacy of medica

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Bagley, Justin C. "Understanding the Diversification of Central American Freshwater Fishes Using Comparative Phylogeography and Species Delimitation." BYU ScholarsArchive, 2014. https://scholarsarchive.byu.edu/etd/5296.

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Phylogeography and molecular phylogenetics have proven remarkably useful for understanding the patterns and processes influencing historical diversification of biotic lineages at and below the species level, as well as delimiting morphologically cryptic species. In this dissertation, I used an integrative approach coupling comparative phylogeography and coalescent-based species delimitation to improve our understanding of the biogeography and species limits of Central American freshwater fishes. In Chapter 1, I conducted a literature review of the contributions of phylogeography to understan

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Johnston, Stuart T. "Mathematical models for quantifying collective cell behaviour." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/109793/1/Stuart_Johnston_Thesis.pdf.

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Collective behaviour is critical to a variety of biological and ecological processes, including tumour invasion, wound healing and spreading of invasive species. This thesis investigated mathematical models of collective cell behaviour, with an aim to develop techniques for applying these models to experimental data to obtain quantitative insight from experiments, and to develop novel models that accurately incorporate cellular mechanisms. We determined various appropriate techniques to extract quantitative information about cell movement and cell proliferation, given particular experimental d

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Schnatter, Sylvia. "Integration-based Kalman-filtering for a Dynamic Generalized Linear Trend Model." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1991. http://epub.wu.ac.at/424/1/document.pdf.

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The topic of the paper is filtering for non-Gaussian dynamic (state space) models by approximate computation of posterior moments using numerical integration. A Gauss-Hermite procedure is implemented based on the approximate posterior mode estimator and curvature recently proposed in 121. This integration-based filtering method will be illustrated by a dynamic trend model for non-Gaussian time series. Comparision of the proposed method with other approximations ([15], [2]) is carried out by simulation experiments for time series from Poisson, exponential and Gamma distributions. (author's abst

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Clark, Andrew Robert James. "Multi-objective ROC learning for classification." Thesis, University of Exeter, 2011. http://hdl.handle.net/10036/3530.

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Receiver operating characteristic (ROC) curves are widely used for evaluating classifier performance, having been applied to e.g. signal detection, medical diagnostics and safety critical systems. They allow examination of the trade-offs between true and false positive rates as misclassification costs are varied. Examination of the resulting graphs and calcu- lation of the area under the ROC curve (AUC) allows assessment of how well a classifier is able to separate two classes and allows selection of an operating point with full knowledge of the available trade-offs. In this thesis a multi-obj

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Williams, Trevor J. "Synthesizing Phylogeography and Community Ecology to Understand Patterns of Community Diversity." BYU ScholarsArchive, 2021. https://scholarsarchive.byu.edu/etd/9176.

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Community ecology is the study of the patterns and processes governing species abundance, distribution, and diversity within and between communities. Likewise, phylogeography is the study of the historic processes controlling genetic diversity across space. Both fields investigate diversity, albeit at different temporal, spatial and taxonomic scales and therefore have varying assumptions. Community ecology typically focuses on contemporary mechanisms whereas phylogeography studies historic ones. However, new research has discovered that both genetic and community diversity can be influenced by

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Browning, Alexander P. "Stochastic mathematical models of cell proliferation assays." Thesis, Queensland University of Technology, 2017. https://eprints.qut.edu.au/110808/1/Alexander_Browning_Thesis.pdf.

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Cell proliferation assays are routinely used to study collective cell behaviour, and can be interpreted with mathematical models. In this thesis, we apply a computational Bayesian technique to calibrate stochastic discrete mathematical models of cell migration and cell proliferation in the context of a cell proliferation assay. Initially, we use a lattice-based model to explore the optimal duration of a cell proliferation assay. Next, we estimate the parameters in a lattice-free model using three independent experimental data sets. Our model is able to both describe and predict the evolution o

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Frühwirth-Schnatter, Sylvia. "Applied State Space Modelling of Non-Gaussian Time Series using Integration-based Kalman-filtering." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 1993. http://epub.wu.ac.at/1558/1/document.pdf.

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The main topic of the paper is on-line filtering for non-Gaussian dynamic (state space) models by approximate computation of the first two posterior moments using efficient numerical integration. Based on approximating the prior of the state vector by a normal density, we prove that the posterior moments of the state vector are related to the posterior moments of the linear predictor in a simple way. For the linear predictor Gauss-Hermite integration is carried out with automatic reparametrization based on an approximate posterior mode filter. We illustrate how further topics in applied state

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Baragatti, Meïli. "Sélection bayésienne de variables et méthodes de type Parallel Tempering avec et sans vraisemblance." Thesis, Aix-Marseille 2, 2011. http://www.theses.fr/2011AIX22100/document.

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Cette thèse se décompose en deux parties. Dans un premier temps nous nous intéressons à la sélection bayésienne de variables dans un modèle probit mixte.L'objectif est de développer une méthode pour sélectionner quelques variables pertinentes parmi plusieurs dizaines de milliers tout en prenant en compte le design d'une étude, et en particulier le fait que plusieurs jeux de données soient fusionnés. Le modèle de régression probit mixte utilisé fait partie d'un modèle bayésien hiérarchique plus large et le jeu de données est considéré comme un effet aléatoire. Cette méthode est une extension de

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Chu, Yue. "SVD-BAYES: A SINGULAR VALUE DECOMPOSITION-BASED APPROACH UNDER BAYESIAN FRAMEWORK FOR INDIRECT ESTIMATION OF AGE-SPECIFIC FERTILITY AND MORTALITY." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1609638415015896.

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Chowdhury, Anupam. "A framework for determining rainfall parameters for stormwater quality treatment system design." Thesis, Queensland University of Technology, 2018. https://eprints.qut.edu.au/120286/1/Anupam_Chowdhury_Thesis.pdf.

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This study developed an innovative stormwater quality treatment design framework for effective mitigation of urban stormwater pollution. The research method is primarily based on a stormwater quality modelling exercise and an extensive statistical analysis for defining the relationships among rainfall, catchment and stormwater quality characteristics. The identified relationships were translated into a framework, enabling the determination of rainfall parameters and treatment system design specifications. Adopting this framework will enhance treatment system performances leading to greater pro

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