Peter .J. Bickel, Kjell A. Doksum

"While other general statistics texts at a similar level touch on some of the topics covered in this book, none of them cover the modern material in this book with comparable depth. As such it is certainly a valuable contribution to our advanced literature on theoretical statistics."~RobertW. Keener, University of Michigan

• Volume I: Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance. Testing and Confidence Regions. Asymptotic Approximations. Inference in the Multiparameter Case. Appendices. Index. Volume II: Introduction to Volume II. Inference When the Number of Parameters Is Large. Distribution-Free, Unbiased and Equivariant Procedures. Inference in Semiparametric Models. Monte Carlo Methods. Nonparametric Inference for Functions of One Variable. Prediction and Machine Learning. Appendix D. Supplements to Text. Solutions for Vol. II. Subject Index.

Peter .J. Bickel, Kjell A. Doksum

"While other general statistics texts at a similar level touch on some of the topics covered in this book, none of them cover the modern material in this book with comparable depth. As such it is certainly a valuable contribution to our advanced literature on theoretical statistics."~RobertW. Keener, University of Michigan

• Volume I: Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance. Testing and Confidence Regions. Asymptotic Approximations. Inference in the Multiparameter Case. Appendices. Index. Volume II: Introduction to Volume II. Inference When the Number of Parameters Is Large. Distribution-Free, Unbiased and Equivariant Procedures. Inference in Semiparametric Models. Monte Carlo Methods. Nonparametric Inference for Functions of One Variable. Prediction and Machine Learning. Appendix D. Supplements to Text. Solutions for Vol. II. Subject Index.

Peter .J. Bickel, Kjell A. Doksum

"While other general statistics texts at a similar level touch on some of the topics covered in this book, none of them cover the modern material in this book with comparable depth. As such it is certainly a valuable contribution to our advanced literature on theoretical statistics."~RobertW. Keener, University of Michigan

• Volume I: Statistical Models, Goals, and Performance Criteria. Methods of Estimation. Measures of Performance. Testing and Confidence Regions. Asymptotic Approximations. Inference in the Multiparameter Case. Appendices. Index. Volume II: Introduction to Volume II. Inference When the Number of Parameters Is Large. Distribution-Free, Unbiased and Equivariant Procedures. Inference in Semiparametric Models. Monte Carlo Methods. Nonparametric Inference for Functions of One Variable. Prediction and Machine Learning. Appendix D. Supplements to Text. Solutions for Vol. II. Subject Index.