Generalized, Linear, and Mixed Models, Vol. 1
Charles E. McCulloch, Shayle R. Searle
For graduate students and practicing statisticians, McCulloch (biostatistics, U. of California-San Francisco) and Searle (biometry, Cornell U.) begin by reviewing the basics of linear models and linear mixed models, in which the variance structure is based on random effects and their variance components. Then they head into the more difficult terrain of generalized linear models, generalized linear mixed models, and even some nonlinear models. The early chapters could provide a core for a one-quarter or one-semester course, or part of a course on linear models.
Categorie:
Anno:
2001
Edizione:
1
Casa editrice:
Wiley-Interscience
Lingua:
english
Pagine:
358
ISBN 10:
047119364X
ISBN 13:
9780471193647
Collana:
Wiley Series in Probability and Statistics
File:
PDF, 13.79 MB
IPFS:
,
english, 2001