Can I read Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series) on EtoBox?

Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series) by Dipak K. Dey, Sujit K. Ghosh, Bani K. Mallick is a nonfiction available to read on EtoBox.

What is Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series) about?

<p><p>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.</p> <h3>booknews</h3> <p>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, Covering Random Effects In Generalized Linear Mixed Models (glmms) With Explained Examples. Considers Parametric And Semiparametric Approaches To Overdispersed Glms, Applies Bayesian Glms To Us Mortality Data, And Presents Methods Of Analyzing Correlated Binary Data Using Latent Variables. Des

Who reads Generalized Linear Models: A Bayesian Perspective (Chapman & Hall/CRC Biostatistics Series)?

Author

Dipak K. Dey, Sujit K. Ghosh, Bani K. Mallick

Publisher

CRC Press LLC

Published

2000

Language

EN

ISBN

9780585389691

Category

nonfiction

Subjects

Mathematics, Medical, Science