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[Download PDF.oHon] Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics)

[Download PDF.oHon] Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics)

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A valuable overview of the most important ideas and results in statistical modeling Written by a highly-experienced author,Foundations of Linear and Generalized Linear Modelsis a clear and comprehensive guide to the key concepts and results of linearstatistical models. The book presents a broad, in-depth overview of the most commonly usedstatistical models by discussing the theory underlying the models, R software applications,and examples with crafted models to elucidate key ideas and promote practical modelbuilding. The book begins by illustrating the fundamentals of linear models, such as how the model-fitting projects the data onto a model vector subspace and how orthogonal decompositions of the data yield information about the effects of explanatory variables. Subsequently, the book covers the most popular generalized linear models, which include binomial and multinomial logistic regression for categorical data, and Poisson and negative binomial loglinear models for count data. Focusing on the theoretical underpinnings of these models,Foundations ofLinear and Generalized Linear Modelsalso features: An introduction to quasi-likelihood methods that require weaker distributional assumptions, such as generalized estimating equation methods An overview of linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian modeling, and extensions to handle problematic cases such as high dimensional problems Numerous examples that use R software for all text data analyses More than 400 exercises for readers to practice and extend the theory, methods, and data analysis A supplementary website with datasets for the examples and exercises An invaluable textbook for upper-undergraduate and graduate-level students in statistics and biostatistics courses,Foundations of Linear and Generalized Linear Modelsis also an excellent reference for practicing statisticians and biostatisticians, as well as anyone who is interested in learning about the most important statistical models for analyzing data. Time Series Analysis for Business Forecasting Effective Modeling for Good Decision-Making What is a model? A Model is an external and explicit representation of a part of reality as it is seen by individuals who Statistics Current - Textbook - Quest Support Area between 0 and z 000 001 002 003 004 005 006 007 008 009 ; 00: 00000: 00040: 00080: 00120: 00160: 00199: 00239: 00279: 00319: 00359: 01: 00398 Damiano Brigo - Imperial College London Back to scientific/academic works Back to top Probability Statistics Nonlinear Filtering Stochastic Differential and Information Geometry Home - Springer Featured Book Consequences of Microbial Interactions with Hydrocarbons Oils and Lipids: Production of Fuels and Chemicals Published 2017 New books and journals Matrix (mathematics) - Wikipedia In mathematics a matrix (plural matrices) is a rectangular array of numbers symbols or expressions arranged in rows and columns For example the dimensions of Mathematics Journals Printed Journals - Math on the Web big list of journals Printed Journals with Mathematics and Internet sites Over 650 websites of printed journals containing tables of contents abstracts Probability -- from Wolfram MathWorld Probability Probability is the branch of mathematics that studies the possible outcomes of given events together with the outcomes' relative likelihoods and Stochastic process - Wikipedia One of the simplest stochastic processes is the Bernoulli process which is a sequence of independent and identically distributed (iid) random variables where each Statistical Inference (and What is Wrong With Classical Statistical Inference (and What is Wrong With Classical Statistics) Scope This page concerns statistical inference as described by the most prominent and mainstream Books in the Mathematical Sciences This site is intended as a resource for university students in the mathematical sciences Books are recommended on the basis of readability and other pedagogical value
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