5 Generalized Linear Models

Nonparametric Regression and Generalized Linear Models: A roughness penalty approach (Repost)

P.J. Green, Bernard. W. Silverman, "Nonparametric Regression and Generalized Linear Models: A roughness penalty approach"
1993 | pages: 194 | ISBN: 0412300400 | PDF | 4,1 mb

An Introduction to Generalized Linear Models [Repost]  eBooks & eLearning

Posted by tanas.olesya at March 22, 2016
An Introduction to Generalized Linear Models [Repost]

An Introduction to Generalized Linear Models, Second Edition by Annette J. Dobson
English | 28 Nov. 2001 | ISBN: 1584881658 | 221 Pages | PDF | 1 MB

Generalized linear models provide a unified theoretical and conceptual framework for many of the most commonly used statistical methods.
Generalized Linear Models, Second Edition (Scan.) by P. McCullagh

Generalized Linear Models, Second Edition (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) by P. McCullagh
English | Aug 1, 1989 | ISBN: 0412317605 | 526 Pages | PDF | 19 MB

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural…
Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood by John A. Nelder [Repost]

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood (Chapman & Hall/CRC Monographs on Statistics & Applied Probability) by John A. Nelder
English | July 13, 2006 | ISBN: 1584886315 | 411 Pages | PDF | 6 MB

Since their introduction in 1972, generalized linear models (GLMs) have proven useful in the generalization of classical normal models. Presenting methods for fitting GLMs with random effects to data, Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood explores a wide range…
Generalized Linear Models: with Applications in Engineering and the Sciences, 2nd edition

Generalized Linear Models: with Applications in Engineering and the Sciences
by Raymond H. Myers, Douglas C. Montgomery
English | 2010 | ISBN: 0470454636 | 496 pages | PDF | 28.11 MB
An Introduction to Generalized Linear Models, Second Edition

An Introduction to Generalized Linear Models, Second Edition by Annette J. Dobson
Chapman and Hall/CRC; 2 edition | November 28, 2001 | English | ISBN: 1584881658 | 240 pages | PDF | 2 MB

Generalized linear models provide a unified theoretical and conceptual framework for many of the most commonly used statistical methods. In the ten years since publication of the first edition of this bestselling text, great strides have been made in the development of new methods and in software for generalized linear models and other closely related models.
Non-Life Insurance Pricing with Generalized Linear Models (repost)

Non-Life Insurance Pricing with Generalized Linear Models
by Esbjorn Ohlsson and Bjorn Johansson
English | 2010 | ISBN: 3642107907 | 174 pages | PDF | 1.27 MB
Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood (repost)

Generalized Linear Models with Random Effects: Unified Analysis via H-likelihood
Chapman & Hall/CRC | 2006 | ISBN: 1584886315 | 416 pages | PDF| 5,4 MB
Non-Life Insurance Pricing with Generalized Linear Models (Repost)

Non-Life Insurance Pricing with Generalized Linear Models
Publisher: Springer | ISBN: 3642107907 | edition 2010 | PDF | 174 pages | 1,7 mb

Non-life insurance pricing is the art of setting the price of an insurance policy, taking into consideration varoius properties of the insured object and the policy holder. Introduced by British actuaries generalized linear models (GLMs) have become today a the standard aproach for tariff analysis.

Generalized Linear Models: A Bayesian Perspective (Biostatistics)  

Posted by kalyan1232008 at March 26, 2009
Generalized Linear Models: A Bayesian Perspective (Biostatistics)

Dipak K. Dey " Generalized Linear Models: A Bayesian Perspective (Biostatistics) "
CRC; 1 edition | May 25, 2000 | English | ISBN-10: 0824790340 | 423 pages | 6.0 MB

This volume describes how to conceptualize, perform, and critique traditional generalized linear models (GLMs) from a Bayesian perspective and how to use modern computational methods to summarize inferences using simulation. Introducing dynamic modeling for GLMs and containing over 1000 references and equations, Generalized Linear Models considers parametric and semiparametric approaches to overdispersed GLMs, presents methods of analyzing correlated binary data using latent variables. It also proposes a semiparametric method to model link functions for binary response data, and identifies areas of important future research and new applications of GLMs.