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Dissertations / Theses on the topic 'Data count'

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1

Osuna, Echavarría Leyre Estíbaliz. "Semiparametric Bayesian Count Data Models." Diss., lmu, 2004. http://nbn-resolving.de/urn:nbn:de:bvb:19-25573.

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2

He, Xin. "Semiparametric analysis of panel count data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4774.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on November 27, 2007) Vita. Includes bibliographical references.
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3

Quoreshi, Shahiduzzaman. "Modelling high frequency financial count data /." Umeå : Umeå University, 2005. http://swopec.hhs.se/umnees/abs/umnees0656.htm.

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4

Hellström, Jörgen. "Count data modelling and tourism demand." Doctoral thesis, Umeå universitet, Institutionen för nationalekonomi, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-82168.

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This thesis consists of four papers concerning modelling of count data and tourism demand. For three of the papers the focus is on the integer-valued autoregressive moving average model class (INARMA), and especially on the ENAR(l) model. The fourth paper studies the interaction between households' choice of number of leisure trips and number of overnight stays within a bivariate count data modelling framework. Paper [I] extends the basic INAR(1) model to enable more flexible and realistic empirical economic applications. The model is generalized by relaxing some of the model's basic independe
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Wan, Chung-him, and 溫仲謙. "Analysis of zero-inflated count data." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2009. http://hub.hku.hk/bib/B43703719.

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6

Chanialidis, Charalampos. "Bayesian mixture models for count data." Thesis, University of Glasgow, 2015. http://theses.gla.ac.uk/6371/.

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Regression models for count data are usually based on the Poisson distribution. This thesis is concerned with Bayesian inference in more flexible models for count data. Two classes of models and algorithms are presented and studied in this thesis. The first employs a generalisation of the Poisson distribution called the COM-Poisson distribution, which can represent both overdispersed data and underdispersed data. We also propose a density regression technique for count data, which, albeit centered around the Poisson distribution, can represent arbitrary discrete distributions. The key contribu
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7

Zhuang, Lili. "Bayesian Dynamical Modeling of Count Data." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1315949027.

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8

Gao, Dexiang. "Analysis of clustered longitudinal count data /." Connect to full text via ProQuest. Limited to UCD Anschutz Medical Campus, 2007.

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Thesis (Ph.D. in Analytic Health Sciences, Department of Preventive Medicine and Biometrics) -- University of Colorado Denver, 2007.<br>Typescript. Includes bibliographical references (leaves 75-77). Free to UCD affiliates. Online version available via ProQuest Digital Dissertations;
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9

Wan, Chung-him. "Analysis of zero-inflated count data." Click to view the E-thesis via HKUTO, 2009. http://sunzi.lib.hku.hk/hkuto/record/B43703719.

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10

Fernández, Fontelo Amanda. "New models of count data with applications." Doctoral thesis, Universitat Autònoma de Barcelona, 2018. http://hdl.handle.net/10803/666009.

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Donat que les dades de recompte es troben en molt fenòmens reals, la necessitat de mètodes i tècniques de qualitat per modelitzar i analitzar aquest tipus de dades és completament indiscutible. En aquest sentit, durant els últims anys, s’han trobat molts articles a la literatura dins dels que s’han desenvolupat tant mètodes bαsics com més generals per l’anàlisi d’aquestes dades. Tot i que a la literatura hi ha un ampli ventall de treballs que tracten alguns dels problemes més rellevants de les dades de recompte, molts altres problemes encara no s’han abordat. Aquesta tesi doctoral té la fina
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Crowe, Brenda. "Seasonal and calendar estimation for count data." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ27901.pdf.

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12

Kalktawi, Hadeel Saleh. "Discrete Weibull regression model for count data." Thesis, Brunel University, 2017. http://bura.brunel.ac.uk/handle/2438/14476.

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Data can be collected in the form of counts in many situations. In other words, the number of deaths from an accident, the number of days until a machine stops working or the number of annual visitors to a city may all be considered as interesting variables for study. This study is motivated by two facts; first, the vital role of the continuous Weibull distribution in survival analyses and failure time studies. Hence, the discrete Weibull (DW) is introduced analogously to the continuous Weibull distribution, (see, Nakagawa and Osaki (1975) and Kulasekera (1994)). Second, researchers usually fo
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13

Zeileis, Achim, Christian Kleiber, and Simon Jackman. "Regression Models for Count Data in R." Department of Statistics and Mathematics, WU Vienna University of Economics and Business, 2007. http://epub.wu.ac.at/1168/1/document.pdf.

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The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of zero-inflated and hurdle regression models in the functions zeroinfl() and hurdle() from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both model c
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14

Zeileis, Achim, Christian Kleiber, and Simon Jackman. "Regression Models for Count Data in R." Foundation for Open Access Statistics, 2008. http://epub.wu.ac.at/4986/1/Zeileis_etal_2008_JSS_Regression%2DModels%2Dfor%2DCount%2DData%2Din%2DR.pdf.

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The classical Poisson, geometric and negative binomial regression models for count data belong to the family of generalized linear models and are available at the core of the statistics toolbox in the R system for statistical computing. After reviewing the conceptual and computational features of these methods, a new implementation of hurdle and zero-inflated regression models in the functions hurdle() and zeroinfl() from the package pscl is introduced. It re-uses design and functionality of the basic R functions just as the underlying conceptual tools extend the classical models. Both hurdle
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15

Nguyen, Thi Kim Hue. "Structure learning of graphs for count data." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3421952.

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Biological processes underlying the basic functions of a cell involve complex interactions between genes. From a technical point of view, these interactions can be represented through a graph where genes and their connections are, respectively, nodes and edges. The main research objective of this thesis is to develop a statistical framework for modelling the interactions between genes when the activity of genes is measured on a discrete scale. We propose several algorithms. First, we define an algorithm for learning the structure of a undirected graph, proving its theoretical consistence in
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16

Duan, Yuanyuan. "Statistical Predictions Based on Accelerated Degradation Data and Spatial Count Data." Diss., Virginia Tech, 2014. http://hdl.handle.net/10919/56616.

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This dissertation aims to develop methods for statistical predictions based on various types of data from different areas. We focus on applications from reliability and spatial epidemiology. Chapter 1 gives a general introduction of statistical predictions. Chapters 2 and 3 investigate the photodegradation of an organic coating, which is mainly caused by ultraviolet (UV) radiation but also affected by environmental factors, including temperature and humidity. In Chapter 2, we identify a physically motivated nonlinear mixed-effects model, including the effects of environmental variables, to des
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Leonte, Daniela School of Mathematics UNSW. "Flexible Bayesian modelling of gamma ray count data." Awarded by:University of New South Wales. School of Mathematics, 2003. http://handle.unsw.edu.au/1959.4/19147.

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Bayesian approaches to prediction and the assessment of predictive uncertainty in generalized linear models are often based on averaging predictions over different models, and this requires methods for accounting for model uncertainty. In this thesis we describe computational methods for Bayesian inference and model selection for generalized linear models, which improve on existing techniques. These methods are applied to the building of flexible models for gamma ray count data (data measuring the natural radioactivity of rocks) at the Castlereagh Waste Management Centre, which served as a ha
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18

Bailey, Daniel John. "Data mining of early day motions and multiscale variance stabilisation of count data." Thesis, University of Bristol, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.492552.

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19

Peng, Jin. "Count Data Models for Injury Data from the National Health Interview Survey (NHIS)." The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365780835.

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20

Wan, Wai-yin. "Analysis of Poisson count data using Geometric Process model." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B37836493.

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21

Wan, Wai-yin, and 溫慧妍. "Analysis of Poisson count data using Geometric Process model." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B37836493.

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22

Fazio, Luna Boris Manuel. "Endpoint-inflated beta-binomial regression for correlated count data." Master's thesis, Pontificia Universidad Católica del Perú, 2019. http://hdl.handle.net/20.500.12404/18680.

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El modelo de regresión binomial con in acción en los extremos permite modelar datos de conteo acotados en los que una alta proporción de las observaciones se encuentra en los extremos. Extendemos el modelo considerando una función de enlace de logit ordenado, la cual aprovecha la información de orden implícita en las probabilidades de in acción y exploramos el uso de efectos aleatorios y marginalización para manejar la presencia de observaciones repetidas. Empleamos un conjunto de datos previamente analizado en la literatura mediante un modelo de regresión binomial con in acción en los
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23

Shobe, Kristin N. "Variable sampling intervals for control charts using count data." Thesis, Virginia Polytechnic Institute and State University, 1988. http://hdl.handle.net/10919/52076.

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This thesis examines the use of variable sampling intervals as they apply to control charts that use count data. Papers by Reynolds, Arnold, and R. Amin developed properties for charts with an underlying normal distribution. These properties are extended in this thesis to accommodate an underlying Poisson distribution.<br>Master of Science
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Patuzzi, Ilaria. "16S rRNA gene sequencing sparse count matrices: a count data simulator and optimal pre-processing pipelines." Doctoral thesis, Università degli studi di Padova, 2018. http://hdl.handle.net/11577/3426369.

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The study of microbial communities has deeply changed since it was firstly introduced in the 17th century. In the late 1970s, a breakthrough in the way bacterial communities were studied was brought by the discovery that ribosomal RNA (rRNA) genes could be used as molecular markers to perform organisms classification. Some decades later, the advent of DNA sequencing technology revolutionized the study of microbial communities, permitting a culture-independent view on the overall community contained within a sample. Today, one of the most widely used approaches for microbial communities profili
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25

Grunow, Nathan Daniel, and Nathan Daniel Grunow. "Analysis of Recurrent Polyp Data in the Presence of Misclassification." Thesis, The University of Arizona, 2016. http://hdl.handle.net/10150/622835.

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Several standard methods are available to analyze and estimate parameters of count data. None of these methods are designed to account for potential misclassification of the data, where counts are observed or recorded as higher or lower than their actual value. These false counts can result in erroneous conclusions and biased estimates. For this paper, a standard estimation model was modified in several ways in order to incorporate each misclassification mechanism. The probability distribution of the observed data was derived and combined with informative distributions for the misclassific
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26

Jansakul, Naratip. "Some aspects of modelling overdispersed and zero-inflated count data." Thesis, University of Exeter, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.364435.

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27

Kaskasamkul, Panicha. "Capture-recapture estimation and modelling for one-inflated count data." Thesis, University of Southampton, 2018. https://eprints.soton.ac.uk/424742/.

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Capture-recapture methods are used to estimate the unknown size of a target population whose size cannot be reasonably enumerated. This thesis proposes the estimators and the models specifically designed to estimate the size of a population for one-inflated capture-recapture count data allowing for heterogeneity. These estimators can assist with overestimation problems occurring from one-inflation that can be seen in several areas of researches. The estimators are developed under three approaches. The first approach is based on a modification by truncating singletons and applying the conventio
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28

Batardière, Bastien. "Machine learning for multivariate analysis of high-dimensional count data." Electronic Thesis or Diss., université Paris-Saclay, 2024. http://www.theses.fr/2024UPASM047.

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Cette thèse traite de la modélisation et de l’analyse de données de comptage de haute dimension dans le cadre des modèles à variables latentes, ainsi que de l’optimisation de tels modèles. Les modèles à variables latentes ont démontré leur efficacité dans la modélisation de structures de dépendance complexes pour les données de comptage, avec le modèle Poisson Log-Normal (PLN) comme exemple principal. Cependant, le modèle PLN ne répond pas aux caractéristiques des jeux de données de comptage réels, principalement en raison de son incapacité à produire un grand nombre de zéros. Nous proposons u
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Canale, Antonio. "Bayesian nonparametric models for count data with applications to customer base management." Doctoral thesis, Università degli studi di Padova, 2012. http://hdl.handle.net/11577/3422460.

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Motivated by the analysis of telecommunications marketing data, which are multidimensional, longitudinal and mostly consisting in counts, this thesis introduces novel Bayesian nonparametric techniques for the estimation of probability mass functions and count stochastic processes. In addition, the theoretical basis of nonparametric mixture models for mixed-scale density estimation are provided. Mixed-scale data consists in joint continuous, count and categorical variables. Although Bayesian nonparametric models for continuous variables are well developed, the literature on related approaches f
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Slotta, Douglas J. "Evalutating Biological Data Using Rank Correlation Methods." Diss., Virginia Tech, 2005. http://hdl.handle.net/10919/27613.

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Analyses based upon rank correlation methods, such as Spearman's Rho and Kendall's Tau, can provide quick insights into large biological data sets. Comparing expression levels between different technologies and models is problematic due to the different units of measure. Here again, rank correlation provides an effective means of comparison between the two techniques. Massively Parallel Signature Sequencing (MPSS) transcript abundance levels to microarray signal intensities for Arabidopsis thaliana are compared. Rank correlations can be applied to subsets as well as the entire set. Results o
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Kreider, Scott Edwin Douglas. "A case study in handling over-dispersion in nematode count data." Manhattan, Kan. : Kansas State University, 2010. http://hdl.handle.net/2097/4248.

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32

Mammana, Alessandro [Verfasser]. "Patterns and algorithms in high-throughput sequencing count data / Alessandro Mammana." Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1108270956/34.

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33

Fasubaa, Akinsola Kunle. "Crime and risk mapping from historic count data in Leicester City." Thesis, University of Leicester, 2007. http://hdl.handle.net/2381/30418.

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This thesis map crime and risk of three crimes from the historic count data in Leicester city from 1999/2003. Observed risk is assess by mapping the crime data and normalized with beat area and population density. As a result of the normalization different pattern emerges, these reveal the ability the GIS to show risk when normalized using different denominators. Objective risk is measured by statistical relationship between the various socio economic factors or variables that are used as surrogate to arrive at the statistical view of risk. To arrive at the statistical view of risk, these vari
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34

Love, Michael I. [Verfasser]. "Statistical analysis of high-throughput sequencing count data / Michael I. Love." Berlin : Freie Universität Berlin, 2013. http://d-nb.info/1043197842/34.

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35

Anan, Orasa. "Capture-recapture modelling for zero-truncated count data allowing for heterogeneity." Thesis, University of Southampton, 2016. https://eprints.soton.ac.uk/402562/.

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Capture-recapture modelling is a powerful tool for estimating an elusive target population size. This thesis proposes four new population size estimators allowing for population heterogeneity. The first estimator is developed under the zero-truncated of generalised Poisson distribution (ZTGP), called the MLEGP. The two parameters of the ZTGP are estimated by using a maximum likelihood with the Expectation-Maximisation algorithm (EM algorithm). The second estimator is the population size estimator under the zero-truncated Conway-Maxwell-Poisson distribution (ZTCMP). The benefits of using the Co
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36

Su, Weizhe. "Bayesian Hidden Markov Model in Multiple Testing on Dependent Count Data." University of Cincinnati / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1613751403094066.

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37

Hua, Lei. "Spline-based sieve semiparametric generalized estimating equation for panel count data." Diss., University of Iowa, 2010. https://ir.uiowa.edu/etd/517.

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In this thesis, we propose to analyze panel count data using a spline-based sieve generalized estimating equation method with a semiparametric proportional mean model E(N(t)|Z) = Λ0(t) eβT0Z. The natural log of the baseline mean function, logΛ0(t), is approximated by a monotone cubic B-spline function. The estimates of regression parameters and spline coefficients are the roots of the spline based sieve generalized estimating equations (sieve GEE). The proposed method avoids assumingany parametric structure of the baseline mean function and the underlying counting process. Selection of an appr
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38

Pihl, Svante, and Leonardo Olivetti. "An Empirical Comparison of Static Count Panel Data Models: the Case of Vehicle Fires in Stockholm County." Thesis, Uppsala universitet, Statistiska institutionen, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-412014.

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In this paper we study the occurrences of outdoor vehicle fires recorded by the Swedish Civil Contingencies Agency (MSB) for the period 1998-2019, and build static panel data models to predict future occurrences of fire in Stockholm County. Through comparing the performance of different models, we look at the effect of different distributional assumptions for the dependent variable on predictive performance. Our study concludes that treating the dependent variable as continuous does not hamper performance, with the exception of models meant to predict more uncommon occurrences of fire. Further
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39

Hintze, Christopher Jerry. "Modeling correlation in binary count data with application to fragile site identification." Texas A&M University, 2005. http://hdl.handle.net/1969.1/4278.

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Available fragile site identification software packages (FSM and FSM3) assume that all chromosomal breaks occur independently. However, under a Mendelian model of inheritance, homozygosity at fragile loci implies pairwise correlation between homologous sites. We construct correlation models for chromosomal breakage data in situations where either partitioned break count totals (per-site single-break and doublebreak totals) are known or only overall break count totals are known. We derive a likelihood ratio test and Neyman’s C( α) test for correlation between homologs when partitioned b
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40

Glaser, Stephanie [Verfasser], and Robert [Akademischer Betreuer] Jung. "Modelling of spatial effects in count data / Stephanie Glaser ; Betreuer: Robert Jung." Hohenheim : Kommunikations-, Informations- und Medienzentrum der Universität Hohenheim, 2017. http://d-nb.info/1129779661/34.

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Jawa, Taghreed Mohammed. "Statistical methods of detecting change points for the trend of count data." Thesis, University of Strathclyde, 2017. http://digitool.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=28854.

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In epidemiology, controlling infection is a crucial element. Since healthcare associated infections (HAIs) are correlated with increasing costs and mortality rates, effective healthcare interventions are required. Several healthcare interventions have been implemented in Scotland and subsequently Health Protection Scotland (HPS) reported a reduction in HAIs [HPS (2015b, 2016a)]. The aim of this thesis is to use statistical methods and change points analysis to detect the time when the rate of HAIs changed and determine which associated interventions may have impacted such rates. Change points
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42

Matzopoulos, Richard. "The body count : using routine mortality surveillance data to drive violence prevention." Doctoral thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/12645.

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Includes bibliographical references.<br>This thesis describes the conceptualisation, development and implementation of a mortuary-based system for the routine collection of information about homicide. It traces the evolution of the system from its conceptualisation in 1994, through various iterations as a city-level research tool, to a national sentinel system pilot, as a multicity all-injury surveillance system, and finally its institutionalisation as a provincial injury mortality surveillance system in the Western Cape. In so doing, it demonstrates that the data arising from medico-legal pos
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Roberts, Clint Douglas. "Imputing Missing Values In Time Series Of Count Data Using Hierarchical Models." The Ohio State University, 2008. http://rave.ohiolink.edu/etdc/view?acc_num=osu1211910310.

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44

Yuksel, Eren. "Heavy Vehicle Classification Analysis Using Length-Based Vehicle Count and Speed Data." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7387.

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There is an increasing demand for application of Intelligent Transportation Systems (ITS) in order to make highways safer and sustainable. Collecting and analyzing traffic stream data are the most important parameters in transportation engineering in enhancing our understanding of traffic congestion and mobility. Classification of the vehicles using traffic data is one of the most essential parameters for traffic management. Of particular interest are heavy vehicles which impact traffic mobility due to their lack of maneuverability and slower speeds. The impact of heavy vehicles on the traffic
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45

Bonafede, Elisabetta <1987&gt. "Differential expression analysis for sequence count data via mixtures of negative binomials." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6741/1/bonafede_elisabetta_tesi.pdf.

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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for
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Bonafede, Elisabetta <1987&gt. "Differential expression analysis for sequence count data via mixtures of negative binomials." Doctoral thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amsdottorato.unibo.it/6741/.

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The recent advent of Next-generation sequencing technologies has revolutionized the way of analyzing the genome. This innovation allows to get deeper information at a lower cost and in less time, and provides data that are discrete measurements. One of the most important applications with these data is the differential analysis, that is investigating if one gene exhibit a different expression level in correspondence of two (or more) biological conditions (such as disease states, treatments received and so on). As for the statistical analysis, the final aim will be statistical testing and for
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47

Inan, Gul. "A Simulation Study On The Comparison Of Methods For The Analysis Of Longitudinal Count Data." Master's thesis, METU, 2009. http://etd.lib.metu.edu.tr/upload/2/12610798/index.pdf.

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The longitudinal feature of measurements and counting process of responses motivate the regression models for longitudinal count data (LCD) to take into account the phenomenons such as within-subject association and overdispersion. One common problem in longitudinal studies is the missing data problem, which adds additional difficulties into the analysis. The missingness can be handled with missing data techniques. However, the amount of missingness in the data and the missingness mechanism that the data have affect the performance of missing data techniques. In this thesis, among the regressi
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48

Jung, Jungah. "Using generalized linear models with a mixed random component to analyze count data." Fogler Library, University of Maine, 2001. http://www.library.umaine.edu/theses/pdf/JungJX2001.pdf.

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49

Fiaccone, Rosemeire L. "Modelling multivariate binary and count data, with application to infant diarrhoea in Brazil." Thesis, Lancaster University, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440384.

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50

Denwood, Matthew James. "A quantitative approach to improving the analysis of faecal worm egg count data." Thesis, University of Glasgow, 2010. http://theses.gla.ac.uk/1837/.

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Analysis of Faecal Egg Count (FEC) and Faecal Egg Count Reduction Test (FECRT) datasets is frequently complicated by a high degree of variability between observations and relatively small sample sizes. In this thesis, statistical issues pertaining to the analysis of FEC and FECRT data are examined, and improved methods of analysis using Bayesian Markov chain Monte Carlo (MCMC) are developed. Simulated data were used to compare the accuracy of MCMC methods to existing maximum likelihood methods. The potential consequences of model selection based on empirical fit were also examined by comparing
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