Distance Correlation Screening Based Model Averaging For Generalized Linear Models
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Distance Correlation Screening Based Model Averaging For Generalized Linear Models
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Author : 許睿育
language : en
Publisher:
Release Date : 2020
Distance Correlation Screening Based Model Averaging For Generalized Linear Models written by 許睿育 and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.
Comparison Of Correlation Partial Correlation And Conditional Mutual Information For Interaction Effects Screening In Generalized Linear Models
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Author : Ji Li
language : en
Publisher:
Release Date : 2018
Comparison Of Correlation Partial Correlation And Conditional Mutual Information For Interaction Effects Screening In Generalized Linear Models written by Ji Li and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Correlation (Statistics) categories.
Numerous screening techniques have been developed in recent years for genome-wide association studies (GWASs) (Moore et al., 2010). In this thesis, a novel model-free screening method was developed and validated by an extensive simulation study. Many screening methods were mainly focused on main effects, while very few studies considered the models containing both main effects and interaction effects. In this work, the interaction effects were fully considered and three different methods (Pearson's Correlation Coefficient, Partial Correlation, and Conditional Mutual Information) were tested and their prediction accuracies were compared. Pearson's Correlation Coefficient method, which is a direct interaction screening (DIS) procedure, tended to incorrectly screen interaction terms as it omits the relationship between main effects and interaction effects. To this end, we proposed to use two new interaction screening procedures, namely Partial Correlation Interaction Screening (PCIS) method and Conditional Mutual Information Interaction Screening (CMIIS) method. The Partial Correlation (PC) could measure association between two variables, while adjusting the effect of one or more extra variables. The Conditional Mutual Information (CMI) is the expected value of the mutual information (MI) of two random variables given the value of a third (Wyner, 1978), while MI is a measure of general dependence. Finally, an illustration and performance comparison of the three screening procedures by simulation studies were made and these procedures were applied to real gene data.
Variable Selection And Model Averaging In Semiparametric Overdispersed Generalized Linear Models
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Author : Remy Cottet
language : en
Publisher:
Release Date : 2008
Variable Selection And Model Averaging In Semiparametric Overdispersed Generalized Linear Models written by Remy Cottet and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with categories.
We express the mean and variance terms in a double exponential regression model as additive functions of the predictors and use Bayesian variable selection to determine which predictors enter the model, and whether they enter linearly or flexibly. When the variance term is null we obtain a generalized additive model, which becomes a generalized linear model if the predictors enter the mean linearly. The model is estimated using Markov chain Monte Carlo simulation and the methodology is illustrated using real and simulated data sets.
Analysis Of Generalized Linear Models For Cluster Correlated Data
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Author : Andrea Gloria Rotnitzky
language : en
Publisher:
Release Date : 1988
Analysis Of Generalized Linear Models For Cluster Correlated Data written by Andrea Gloria Rotnitzky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with categories.
Advances And Innovations In Statistics And Data Science
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Author : Wenqing He
language : en
Publisher: Springer Nature
Release Date : 2022-10-27
Advances And Innovations In Statistics And Data Science written by Wenqing He and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-27 with Science categories.
This book highlights selected papers from the 4th ICSA-Canada Chapter Symposium, as well as invited articles from established researchers in the areas of statistics and data science. It covers a variety of topics, including methodology development in data science, such as methodology in the analysis of high dimensional data, feature screening in ultra-high dimensional data and natural language ranking; statistical analysis challenges in sampling, multivariate survival models and contaminated data, as well as applications of statistical methods. With this book, readers can make use of frontier research methods to tackle their problems in research, education, training and consultation.
Generalized Linear Models For Insurance Rating
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Author : Mark Goldburd
language : en
Publisher:
Release Date : 2016-06-08
Generalized Linear Models For Insurance Rating written by Mark Goldburd and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-08 with categories.
Generalized Linear Mixed Models
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Author : Charles E. McCulloch
language : en
Publisher: IMS
Release Date : 2003
Generalized Linear Mixed Models written by Charles E. McCulloch and has been published by IMS this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
Wiley Series in Probability and Statistics A modern perspective on mixed models The availability of powerful computing methods in recent decades has thrust linear and nonlinear mixed models into the mainstream of statistical application. This volume offers a modern perspective on generalized, linear, and mixed models, presenting a unified and accessible treatment of the newest statistical methods for analyzing correlated, nonnormally distributed data. As a follow-up to Searle's classic, Linear Models, and Variance Components by Searle, Casella, and McCulloch, this new work progresses from the basic one-way classification to generalized linear mixed models. A variety of statistical methods are explained and illustrated, with an emphasis on maximum likelihood and restricted maximum likelihood. An invaluable resource for applied statisticians and industrial practitioners, as well as students interested in the latest results, Generalized, Linear, and Mixed Models features: * A review of the basics of linear models and linear mixed models * Descriptions of models for nonnormal data, including generalized linear and nonlinear models * Analysis and illustration of techniques for a variety of real data sets * Information on the accommodation of longitudinal data using these models * Coverage of the prediction of realized values of random effects * A discussion of the impact of computing issues on mixed models
Experimental Design And Data Analysis For Biologists
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Author : Gerald Peter Quinn
language : en
Publisher: Cambridge University Press
Release Date : 2002-03-21
Experimental Design And Data Analysis For Biologists written by Gerald Peter Quinn and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-03-21 with Mathematics categories.
Regression, analysis of variance, correlation, graphical.
Functional Neuroradiology
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Author : Scott H. Faro
language : en
Publisher: Springer Nature
Release Date : 2023-05-23
Functional Neuroradiology written by Scott H. Faro and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-23 with Medical categories.
This new edition fully updates and expands Faro and Mohamed’s Functional Neuroradiology, a gold standard, comprehensive introduction to the state-of-the-art functional imaging in neuroradiology, including the physical principles and clinical applications of Diffusion, Perfusion, Permeability, MR spectroscopy, Positron Emission Tomography, BOLD fMRI and Diffusion Tensor Imaging. With chapters written by internationally distinguished neuroradiologists, neurologists, psychiatrists, cognitive neuroscientists, and physicists, Functional Neuroradiology is divided into 12 major sections, including: Diffusion and Perfusion Imaging, Magnetic Resonance Spectroscopy and Chemical Exchange Saturation Transfer Imaging, Multi-Modality Functional Neuroradiology, BOLD Functional MRI, Diffusion Tensor Imaging, Presurgical Brain Tumor Mapping, Emerging neuroimaging techniques, Functional Spine and Hydrocephalus imaging, and Neuroanatomical Gray and White matter Brain Atlases. This second edition is fully updated throughout and includes more than 15 new chapters on topics such as: Brain tumor Radiogenomics, CNS Tumor Surveillance and Functional MR Perfusion Imaging, CNS Machine Learning, Focused Ultrasound therapy, TBI Sports Related Injury, and CNS Lymphatic system. By offering readers a complete overview of functional imaging modalities and techniques currently used in patient diagnosis and management, as well as emerging technology, Functional Neuroradiology is a vital information source for physicians and cognitive neuroscientists involved in daily practice and research.
Econometrics
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Author : Bruce Hansen
language : en
Publisher: Princeton University Press
Release Date : 2022-06-28
Econometrics written by Bruce Hansen and has been published by Princeton University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-28 with Business & Economics categories.
The most authoritative and up-to-date core econometrics textbook available Econometrics is the quantitative language of economic theory, analysis, and empirical work, and it has become a cornerstone of graduate economics programs. Econometrics provides graduate and PhD students with an essential introduction to this foundational subject in economics and serves as an invaluable reference for researchers and practitioners. This comprehensive textbook teaches fundamental concepts, emphasizes modern, real-world applications, and gives students an intuitive understanding of econometrics. Covers the full breadth of econometric theory and methods with mathematical rigor while emphasizing intuitive explanations that are accessible to students of all backgrounds Draws on integrated, research-level datasets, provided on an accompanying website Discusses linear econometrics, time series, panel data, nonparametric methods, nonlinear econometric models, and modern machine learning Features hundreds of exercises that enable students to learn by doing Includes in-depth appendices on matrix algebra and useful inequalities and a wealth of real-world examples Can serve as a core textbook for a first-year PhD course in econometrics and as a follow-up to Bruce E. Hansen’s Probability and Statistics for Economists