Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Name: Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data
Brand: Oxford University Press
SKU: 9780199533022
Price: 183.2 EUR
Availability: InStock

Автор: Ludwig Fahrmeir

Език:

Корици: С твърди корици

Издател: Oxford University Press

Наличност: Налично при издателя, по поръчка

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Several recent advances in smoothing and semiparametric regression are presented in this book from a...

Информация за книгата

Автор

Ludwig Fahrmeir

Език

Английски език

Корици

Книга - С твърди корици

Издадена

2011

страници

544

EAN

9780199533022

ISBN

0199533024

Enbook ID

01323354

Издател

Oxford University Press

Теглоt

920

Размери

163 x 233 x 34

Пълно описание

Several recent advances in smoothing and semiparametric regression are presented in this book from a unifying, Bayesian perspective. Simulation-based full Bayesian Markov chain Monte Carlo (MCMC) inference, as well as empirical Bayes procedures closely related to penalized likelihood estimation and mixed models, are considered here. Throughout, the focus is on semiparametric regression and smoothing based on basis expansions of unknown functions and effects in combination with smoothness priors for the basis coefficients. Beginning with a review of basic methods for smoothing and mixed models, longitudinal data, spatial data and event history data are treated in separate chapters. Worked examples from various fields such as forestry, development economics, medicine and marketing are used to illustrate the statistical methods covered in this book. Most of these examples have been analysed using implementations in the Bayesian software, BayesX, and some with R Codes. These, as well as some of the data sets, are made publicly available on the website accompanying this book.

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Bayesian Smoothing and Regression for Longitudinal, Spatial and Event History Data

Информация за книгата

Пълно описание

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