UID:
almafu_9959328819602883
Format:
1 online resource (xi, 573 pages) :
,
illustrations
Edition:
2nd ed.
ISBN:
9780470035931
,
0470035935
,
9780470035948
,
0470035943
Series Statement:
Wiley series in probability and statistics.
Content:
Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters.
Note:
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.
Additional Edition:
Print version: Congdon, P. Bayesian statistical modelling. Chichester, England ; Hoboken, NJ : John Wiley & Sons, ©2006 ISBN 0470018755
Additional Edition:
ISBN 9780470018750
Language:
English
Keywords:
Electronic books.
;
Electronic books.
;
Electronic books.
;
Electronic books.
;
Electronic books.
DOI:
10.1002/9780470035948
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470035948
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470035948
URL:
https://onlinelibrary.wiley.com/doi/book/10.1002/9780470035948
