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 117 for “"Generalized linear models"”.
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Diagnostics for generalized linear models
… model. In this thesis we look at how the generalized linear model has become one of the most important developments in statistics in the last thirty years, and on the adequacy of regression model diagnostics that are meaningful and significant in a generalized linear model context. Some …
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Generalized Linear Models with Nonignorable Missing Covariates
In this thesis, we present an overview of generalized linear models (GLMs) for binary and count data with missing covariates when the missing data mechanism is nonignorable. We use the maximum likelihood method to estimate the parameters in GLMs. We study a set of ML estimating equations for …
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Approximate cross validation for sparse generalized linear models
Cross validation (CV) is an effective yet computationally expensive tool for assessing the out of sample error for many methods in machine learning and statistics. Previous work has shown that methods to approximate CV can be very accurate and computationally cheap, but only for low dimensional …
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Bayesian D-Optimal Design for Generalized Linear Models
… Bayesian D-optimal designs for multi-variable generalized linear models. Particularly, Poisson regression models and logistic regression models are investigated. Designs are examined for a range of prior distributions and the equivalence theorem is used to verify the design optimality. Design …
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P-VALUE BASED VARIABLE SELECTION FOR GENERALIZED LINEAR MODELS
… p-value based methods for variable selection in generalized linear models. Generalized linear models are widely used, but their non-analytic solutions and intricate dependencies create challenges for many existing methods. Addressing these issues, our proposed contributions can select important …
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Bayesian and maximum likelihood methods for some two-segment generalized linear models.
… CP problems using two-segment regression models, such as those based on generalized linear models, are very flexible and widely used. For two-segment Poisson and logistic regression models, misclassification in the response is well known to cause attenuation of key parameters and other …
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Penalized Regression Methods with Application to Generalized Linear Models, Generalized Additive Models, and Smoothing
Recently, penalized regression has been used for dealing problems which found in maximum likelihood estimation such as correlated parameters and a large number of predictors. The main issues in this regression is how to select the optimal model. In this thesis, Schall’s algorithm is proposed as an …
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Understanding Scaled Prediction Variance Using Graphical Methods for Model Robustness, Measurement Error and Generalized Linear Models for Response Surface Designs
… to measurement error and design properties for generalized linear models (GLM). This dissertation presents a graphical method for examining design robustness related to the SPV values using FDS plots by comparing designs across a number of potential models in a pre-specified model space. Scaling …
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On the Efficiency of Designs for Linear Models in Non-regular Regions and the Use of Standard Desings for Generalized Linear Models
… designs for non-regular regions for first order models with interaction for the two- and three-factor case, and using the standard designs in the case of generalized linear models (GLM). The Fraction of Design Space (FDS) technique is proposed as a new graphical evaluation technique that …
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Some topics on robust nonparametric regression and regression quantiles
… in the nonparametric regression and the generalized linear models. The consistency and asymptotic normality of kernel estimates are proved. Simulations on B-spline estimates for nonparametric regression and generalized linear models are provided.
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Some Aspects on Data Modelling
… follow different distributions or statistical models. Change point problems in generalized linear models and distributions of independent random variables are studied respectively. Firstly, to estimate multiple change points in generalized linear models, we convert it into a model selection …
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Vector Generalized Linear Time Series Models with an Implementation in R
… extensions have been proposed involving linear and non-linear structures as part of a huge literature, for instance, the vector-ARMA class for multivariate TS and the ARCH-GARCH-type models for heteroskedasticity. The result has been an explosion of TS models and inference schemes having …
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A profile of the auditory function of children with TB receiving ototoxic medication at Brooklyn Chest Hospital
… were analysed using descriptive statistics and Generalized Linear Models. The results suggest that 55% of children had middle ear abnormality and 48% had hearing loss. The degree of hearing loss ranged from mild to profound in 41 % of the cases while 59% had hearing within the normal range with …
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Decoding Neural Processing of Linguistic Features From Large-Scale Intracranial Recordings and Naturalistic Language Stimuli
… dataset of recorded brain activity, we fit Generalized Linear Models (GLM) to map language and vision stimuli to induced brain activity. This framework allows us to localize processing areas in the brain per feature, as well as explore the temporal dynamics of this processing. Findings …
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High dimensional feature selection under interactive models
… EBIC (Chen and Chen, 2008) to interactive models and .explore its selection consistency. With the application of EBIC, we develop a novel feature selection procedure, called sequential L1 regularization algorithm (SLR), under high dimensional space by considering both the main effect …
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Influence of Habitat Disturbances on Endemic Grassland Bird Distributions in Loamy Ecological Range Sites at Canadian Forces Base Suffield, Alberta
… by vegetation structure. Spatial autocovariate generalized linear models were developed for four primary endemic grassland bird species from point count data collected in loamy ecological range sites during spring 2013 and 2014. These models indicated habitat disturbances influenced bird …
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Shared Haplotype Length Regression and Its Application
… under positive selection. My statistics employs generalized linear models and generalized estimating equations to test for associations between shared haplotype lengths and traits. Due to the possibility of high number of haplotypes in the model, I also proposed an extension of the statistics …
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Improving applicability of the non-monotone unified estimate for missing data
… inverse probability weighting that uses "working models" to extract information from individuals with partially observed data. When the probability an individual has missing data can be accurately modeled but the distribution of the data is difficult to model the unified approach is an attractive …
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Essays in Problems in Sequential Decisions and Large-Scale Randomized Algorithms
… Hadamard transform, to solve a wide class of generalized linear models.
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Intersectional social identity in Early Iron Age Dolenjska : a statistical analysis of grave goods from Kapiteljska njiva in Novo Mesto, Slovenia
… between the variables is tested using generalized linear models and chi-squared tests of association. Results indicate that expressions of gender and status are closely related, with women demonstrating status in ways that are most visible archaeologically. The role of weaver and …
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