Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition presents fundamental, classical statistical concepts at the doctorate level. It covers estimation, prediction, testing, confidence sets, Bayesian analysis, and the general approach of decision theory. This edition gives careful proofs of major results and explains how the theory sheds light on the properties of practical methods.The book first discusses non- and semiparametric models before covering parameters and parametric models. It then offers a detailed treatment of maximum likelihood estimates (MLEs) and examines the theory of testing and confidence regions, including optimality theory for estimation and elementary robustness considerations. It next presents basic asymptotic approximations with one-dimensional parameter models as examples. The book also describes inference in multivariate (multiparameter) models, exploring asymptotic normality and optimality of MLEs, Wald and Rao statistics, generalized linear models, and more.Mathematical Statistics: Basic Ideas and Selected Topics, Volume II will be published in 2015. It will present important statistical concepts, methods, and tools not covered in Volume I.

zlib/Science (General)/Peter J. Bickel, Kjell A. Doksum/Mathematical Statistics Basic Ideas and Selected Topics Volume I_2821856.pdf

Peter J. Bickel, Kjell A. Doksum

Taylor & Francis Group

Chapman and Hall/CRC

Prentice Hall

Texts in statistical science, 2nd ed, Upper Saddle River, N.J, ©2001-

Texts in statistical science, Second edition, Boca Raton, FL, 2015

Texts in Statistical Science, I, 2, 2015

United States, United States of America

CRC Press LLC, Boca Raton, FL, 2015

lg2358968

2018-04-25