Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics)

Foundations of Linear and Generalized Linear Models (Wiley Series in Probability and Statistics)


A important assessment of an important principles and ends up in statistical modeling

Written by way of a highly-experienced author, Foundations of Linear and Generalized Linear Models is a transparent and complete consultant to the most important recommendations and result of linearstatistical versions. The publication provides a vast, in-depth evaluation of the main as a rule usedstatistical versions through discussing the speculation underlying the versions, R software program applications,and examples with crafted types to explain key principles and advertise useful modelbuilding.

The e-book starts by means of illustrating the basics of linear versions, reminiscent of how the model-fitting tasks the information onto a version vector subspace and the way orthogonal decompositions of the information yield information regarding the results of explanatory variables. accordingly, the booklet covers the most well-liked generalized linear types, which come with binomial and multinomial logistic regression for specific information, and Poisson and destructive binomial loglinear versions for count number facts. targeting the theoretical underpinnings of those models, Foundations ofLinear and Generalized Linear Models also features:

  • An advent to quasi-likelihood tools that require weaker distributional assumptions, akin to generalized estimating equation methods
  • An review of linear combined versions and generalized linear combined versions with random results for clustered correlated facts, Bayesian modeling, and extensions to deal with troublesome circumstances similar to excessive dimensional problems
  • Numerous examples that use R software program for all textual content facts analyses
  • More than four hundred routines for readers to perform and expand the idea, equipment, and information analysis
  • A supplementary site with datasets for the examples and exercises

a useful textbook for upper-undergraduate and graduate-level scholars in information and biostatistics courses, Foundations of Linear and Generalized Linear Models is additionally a very good reference for training statisticians and biostatisticians, in addition to an individual who's drawn to studying in regards to the most vital statistical types for reading data.

 

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