33642

Peter Congdon

2nd ed

John Wiley & Sons

xi, 573 p. : ill. ; 25 cm.

Wiley series in probability and statistics

Includes bibliographical references and index

Introduction : the Bayesian method, its benefits and implementation -- Bayesian model choice, comparison and checking -- The major densities and their application -- Normal linear regression, general linear models and log-linear models -- Hierarchical priors for pooling strength and overdispersed regression modelling -- Discrete mixture priors -- Multinomial and ordinal regression models -- Time series models -- Modelling spatial dependencies -- Nonlinear and nonparametric regression -- Multilevel and panel data models -- Latent variable and structural equation models for multivariate data -- Survival and event history analysis -- Missing data models -- Measurement error, seemingly unrelated regressions, and simultaneous eqations

TI , SE

QA

279.5

.C65

2006

QA 279.5 .C65 2006

c2006