Bayesian smoothing and regression for longitudinal, spatial and event history data /

Bringing together recent advances in smoothing and semiparametric regression from a Bayesian perspective, this book demonstrates, with worked examples, the application of these statistical methods to a variety of fields including forestry development economics, medicine and marketing.

Bibliographic Details
Main Authors:	Fahrmeir, L. (Author), Kneib, Thomas (Author)
Format:	eBook
Language:	English
Language Notes:	English.
Published:	Oxford ; New York : Oxford University Press, 2011.
Series:	Oxford statistical science series ; 36.
Subjects:	Regression analysis. Bayesian statistical decision theory. Smoothing (Statistics) Regression Analysis Analyse de régression. Théorie de la décision bayésienne. Lissage (Statistique) Bayesian statistical decision theory Regression analysis Electronic books.
Online Access:	Connect to the full text of this electronic book

Table of Contents:

1. Introduction: Scope of the Book and Applications
2. Basic Concepts for Smoothing and Semiparametric Regression
3. Generalised Linear Mixed Models
4. Semiparametric Mixed Models for Longitudinal Data
5. Spatial Smothing, Interactions and Geoadditive Regression
6. Event History Data.