Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 75 for “"Zero-inflated"”.
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New Multivariate Zero-Inflated Beta-Binomial Distribution
The multivariate zero-inflated beta-binomial model is significantly important for modelling and analyzing multivariate proportional data with extra zeros. Comparing with the binomial model, the beta-binomial model is a better alternative for explicitly accounting for over-dispersion, and …
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Copula-Based Zero-Inflated Count Time Series Models
… finance. In some cases, a specific count, say zero, may occur more often than usual. Additionally, serial dependence might be found among these counts if they are recorded over time. Overlooking the frequent occurrence of zeros and the serial dependence could lead to false inference. In this …
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Modeling zero-inflated and overdispersed count data: application to in-hospital mortality data
… have a highly right-skewed distribution for non-zero values and possible excess zero counts. Our study aims to examine the association of serum chloride levels at different time points with hospital mortality and to model the length of hospital and ICU stays in conjunction with zero-inflated and …
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Zero-Inflated Models to Identify Transcription Factor Binding Sites in ChIP-seq Experiments
… we propose a negative binomial model (NB), a zero-inflated Poisson model (ZIP) and a zero-inflated negative binomial model (ZINB) for peak-calling. Using real ChIP-seq datasets, we show that ZINB model is the best model for ChIP-seq data. Then we incorporate control data, GC count information, …
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A Simulation Study to Evaluate Bayesian LASSO’s Performance in Zero-Inflated Poisson (ZIP) Models
… count data, it is possible to have excessive zeros in the data in many applications. My thesis concentrates on the variable selection in zero-inflated Poisson (ZIP) models. This thesis work is motivated by Brown et al. (2015), who considered the excessive amount of zero in their data structure …
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Bayesian approach for modeling zero-inflated plant percent covers using spatial left-censored beta regression
… with ecological data is the large number of zeros: most of the time species are not observed at the sampling location. Zeros can be thought to arise from ecological reasons or due to randomness. This problem of zero inflation is well studied for discrete positive data, such as counts and …
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A Bayesian approach to crossed-random-effects mediation analysis for zero-inflated mediators and binary outcomes
… a mediation model with crossed random effects, a zero-inflated mediator, and a binary outcome. With maximum likelihood estimation (MLE), the mediation model could not converge, which was consistent with the previous finding on analyzing CREM with MLE (Huang & Anderson, 2020). Therefore, the …
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Associated factor of mortality rate amongst patients with AIDS and HIV-TB co-infections using zero inflated negative binomial method
… as count data with a preponderance of zeros. Data in the form of counts and proportions arise in many fields such as studies in medicine, public health, toxicology, epidemiology, sociology, psychology, engineering, agriculture and soon. When the dependent variable is a nonnegative count …
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Model-based clustering for multivariate time series of counts
… framework for univariate and multivariate zero-inflated time series of counts and applies the models in a clustering scheme to identify groups of count series with similar behavior. The basic modeling framework used is observation-driven Poisson regression with generalized linear model …
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The economics of military spending, conflict and growth
… examines the determinants of civil war, using a zero-inflated modelling approach to deal with excess zeroes in the dependent variable. Traditional probit and logit models have limited capacity in dealing with this issue and can create misleading results, which is illustrated through replicating …
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Statistical Methods for Genetic Pathway-Based Data Analysis
… model for identifying pathways related to the zero inflated clinical outcomes; the other is to propose a multilevel Gaussian graphical model for exploring both pathway and gene level network structures. For the first problem, we develop a semiparametric model via a Bayesian hierarchical …
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Variable Selection and Hypothesis Testing for High-Dimensional Models in Mental Health Research
… structures, and outcomes exhibiting excess zeros. These characteristics pose significant challenges for variable selection, model estimation, hypothesis testing, and sample size determination, often undermining statistical stability, interpretability, and computational efficiency. This …
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An ecological adjusted random effect model for violent and property crime in Windhoek (2011-2016)
Count data that are zero inflated are often analysed using Zero-Inflated Negative Binomial Generalized Linear Mixed Model (ZTNB-GLMM) when observations are correlated in ways that require random effects. The present study investigates ecological factors influencing Violent and Property crime in …
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An Economic Analysis of Secure Messaging between Patients and Providers
… and continuous models with an excess number of zeros and unobserved individual heterogeneity. This approach is similar to a zero inflated model in the way it deals with excess zeros, but unlike a zero inflated model it is robust to distributional misspecifications. Also, its ability to deal with …
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Bayesian approaches to problems in diagnostic testing and underreported count data.
… Finally, the last chapter extends a zero-inflated Poisson distribution accounting for underreporting into the Bayesian paradigm. We analyze this Bayesian model in multiple simulation studies. When underreporting is inaccurately estimated, model parameter estimation can be biased. …
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Fishery Interaction Modeling of Cetacean Bycatch in the California Drift Gillnet Fishery to Inform a Dynamic Ocean Management Tool
… which cause a large amount of absences (zeros) in each species’ dataset. Using a data-assimilative configuration of the Regional Ocean Modeling System, we determined the capabilities of a flexible machine-learning algorithm to handle these zero-inflated datasets in order to explore the …
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Integrative Approaches in Genomic Analysis: Advancing Epigenetic Prediction, Twas Methodology, and Cell-Type Deconvolution in Spatial Transcriptomics
… in situ on slices of tissue. We present a novel zero-inflated hierarchical generalized transformation (ZI-HGT) model that functions as a noisy transformation for cell-type deconvolution with conditional autoregressive-based deconvolution (CARD). CARD assumes normality of the highly zero-inflated, …
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Count Data Models for Injury Data from the National Health Interview Survey (NHIS)
… using injury count data from 2006-2011 NHIS. The Zero-Inflated Negative Binomial (ZINB) model turns out to be the optimal count data model for our data. The inferences made from the ZINB regression model are compared with those from the logistic regression model. The results indicate that ZINB …
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Legislating Morality: Codes of Ethics and Sanctions Related to Teacher Misconduct
… 12 states over a 10-year period. The author used zero-inflated negative binomial regression and determined that the legislated status and nature of codes of ethics for teachers, average annual teacher salary, states’ right to work status, and union coverage had a relationship with sanctions. …
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Evaluating and comparing Gaussian forecasts for discrete process time series.
… In chapter four we extend our work to the zero-inflated Poisson integer autoregressive process. We conclude with a brief summary and discussion in chapter five.
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