A Graduate Course on Statistical Inference (Hardcover, 1st ed. 2019)

This textbook offers an accessible and comprehensive overview of statistical estimation and inference that reflects current trends in statistical research. It draws from three main themes throughout: the finite-sample theory, the asymptotic theory, and Bayesian statistics. The authors have included a chapter on estimating equations as a means to unify a range of useful methodologies, including generalized linear models, generalized estimation equations, quasi-likelihood estimation, and conditional inference. They also utilize a standardized set of assumptions and tools throughout, imposing regular conditions and resulting in a more coherent and cohesive volume. Written for the graduate-level audience, this text can be used in a one-semester or two-semester course.

General

Imprint:	Springer-Verlag New York
Country of origin:	United States
Series:	Springer Texts in Statistics
Release date:	August 2019
First published:	2019
Authors:	Bing Li • G. Jogesh Babu
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	379
Edition:	1st ed. 2019
ISBN-13:	978-1-4939-9759-6
Categories:	Books > Science & Mathematics > Mathematics > Probability & statistics
LSN:	1-4939-9759-9
Barcode:	9781493997596

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