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 78 for “"Generalized Linear Model"”.
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Semiparametric Methods for the Generalized Linear Model
The generalized linear model (GLM) is a popular model in many research areas. In the GLM, each outcome of the dependent variable is assumed to be generated from a particular distribution function in the exponential family. The mean of the distribution depends on the independent variables. The link …
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Topics on multiple hypotheses testing and generalized linear model
… global test, which guarantees control of generalized familywise error rate (k-FWER) among the selected families. In the second stage, individual hypotheses are tested for each selected families by using some multiple testing procedure, which controls conditional false discovery rate (cFDR) …
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Ill-conditioned information matrices and the generalized linear model: an asymptotically biased estimation approach
In the regression framework of the generalized linear model (Nelder and Wedderburn (1972)), interative maximum likelihood parameter estimation is employed via the method of scoring. This iterative procedure involves a key matrix, the information matrix. Ill-conditioning of the information matrix …
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Diagnostics for generalized linear models
… can capture departures from a parametrized 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 …
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Determination of factors that influence digit preference: A Case study of South African Census 2011 Age-Sex date
… Ratio and Sex Ratio) and multivariate methods (Generalized linear model, Principal Component analysis and Regression analysis) which have been reviewed in detail in the study. This study utilized a full age dataset in single years. Based on the United Nation Age-sex Accuracy Index which was …
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Likelihood and Bayesian signal processing methods for the analysis of auditory neural and behavioral data
Developing a consensus on how to model neural and behavioral responses and to quantify important response properties is a challenging signal processing problem because models do not always adequately capture the data and different methods often yield different estimates of the same response …
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Longitudinal Trends in Early Childhood Napping Behaviours
… children aged 1-6 years, Study One employed a generalized linear model to examine nap patterns over a 6-month period, revealing significant declines in daytime sleep proportion and duration, particularly among regular nappers. Additionally, 4% of children who were not napping at baseline …
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Regression modeling: Latent structure, theories and algorithms
… the data, the thesis invents some new regression modeling methods, provides theoretical background for these newly developed and some other existed ad hoc modeling techniques, and develops associated algorithms. The modeling techniques include scaled link in the class of generalized linear model, …
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Use of Geospatial Methods to Characterize Dispersion of the Emerald Ash Borer in Southern Ontario, Canada
… of Random Forest and GLM known as the Random Generalized Linear Model (RGLM) were applied to EAB data from 2006-2012 across Ontario. Ultimately, three risk maps were created from the 2006-2012 EAB data to validate the prediction dataset from 2013. In terms of model transferability, RGLM had …
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Characterizing electrodermal responses during sleep in a 30-day ambulatory study
… available wearable sensors. In this thesis, we model and analyze electrodermal response (EDR) events (1-5 second peaks in the EDA signal) during sleep in an ambulatory study. In particular, we describe an EDR event detection algorithm and extract shape features from these events to discuss the …
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Analysis of the Repeated Measurement Data using the Hierarchical Clustering and Nonlinear Regression Methods in Asthma Pharmacogenetic Study
… Korea asthmatics and tried to develop a clinical model to predict the drug response to asthma drug. BACKGROUND: Long acting β2-agonists (LABA) is the most powerful bronchodilator and inhaled corticosteroid (ICS) was the most effective anti-inflammatory drug currently available in asthma …
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Atmospheric and spatial drivers of egg abundance in beach nesting shorebirds across an urban-coastal gradient of the Rockaway Peninsula, New York
… habitat availability, and disturbance. A Poisson generalized linear model identified maximum temperature as the dominant factor associated with egg abundance, showing a consistent negative relationship. Elevation had a significant and positive but secondary effect, likely related to reduced …
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Semiparametric Inference
Semi-parametric and nonparametric modeling and inference have been widely studied during the last two decades. In this manuscript, we do statistical inference based on semi-parametric and nonparametric models in several different scenarios. Firstly, we develop a semi-parametric additivity test for …
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Analysis of long-term changes in populations of the Clanwiliam Cedar (Widdringtonia cedarbergensis) using repeat photography
… individuals with sparse foliage cover. A generalized linear model was used to determine the effects of environmental factors on W. cedarbergensis mortality in natural populations.
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Ecological Momentary Assessment of Mechanisms Linking Racial Discrimination and Substance Use in Black College Students
… for the complex EMA survey design, multilevel models were used for analysis. For both aims, a generalized linear model with a Poisson distribution was implemented for alcohol quantity (count), while a generalized linear model with a binomial distribution was applied to all other substances …
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Influence of tree planting guidelines on street tree distribution along bus corridors
… and spacing from street corners. Using a generalized linear model and regulation severity scores, we assessed the impact of these regulations on tree density. The analysis revealed that certain requirements—such as minimum distances between trees, structures, traffic controls, and …
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Long Term Ground Based Precipitation Data Analysis: Spatial and Temporal Variability
… response variables (classifiers) on various models applied to the detection of El Niño Southern Oscillation (ENSO) on California’s seven climate divisions by using modeled and gauge (in-situ/ground) precipitation measurements and various climate indices. Three scientific studies were …
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Model Robust Regression Based on Generalized Estimating Equations
One form of model robust regression (MRR) predicts mean response as a convex combination of a parametric and a nonparametric prediction. MRR is a semiparametric method by which an incompletely or an incorrectly specified parametric model can be improved through adding an appropriate amount of a …
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State-Space Models and Latent Processes in the Statistical Analysis of Neural Data
… chapter we incorporate a latent process to the Generalized Linear Model framework. We develop and apply our framework to estimate the linear filters of an entire population of retinal ganglion cells while taking into account the effects of common-noise the cells might share. We are able to …
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Contributions to Structured Variable Selection Towards Enhancing Model Interpretation and Computation Efficiency
… selection of variables should facilitate the model interpretation and computation efficiency. It is thus important to incorporate domain knowledge of underlying data generation mechanism to select key variables for improving the model performance. However, general variable selection …
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