三个大牛写的书，经典教材。pdf版本，不是高清版（清晰度见sample page），但不妨碍阅读。

The first edition of Theory of Rank Tests (1967) has been the precursor to a unified and theoretically motivated treatise of the basic theory of tests based on ranks of the sample observations. For more than 25 years, it helped raise a generation of statisticians in cultivating their theoretical research in this fertile area, as well as in using these tools in their application oriented research. The present edition not only aims to revive this classical text by updating the findings but also by incorporating several other important areas which were either not properly developed before 1965 or have gone through an evolutionary development during the past 30 years. This edition therefore aims to fulfill the needs of academic as well as professional statisticians who want to pursue nonparametrics in their academic projects, consultation, and applied research works.

Key Features
* Asymptotic Methods
* Nonparametrics
* Convergence of Probability Measures
* Statistical Inference

Editorial Reviews
Review
"This book is an updated second edition of the famous and outstanding textbook of Hájek and Šidák. The statistical community is grateful to Šidák and Sen, who continued Hájek's work by their worthwhile treatment of the subject. The present revised and extended edition now presents the topic in a modern form and it is again a landmark."
--MATHEMATICAL REVIEWS, Issue 2000h
"...statisticians interested in rigorous analysis of the limiting case are likely to find valuable informatin in this book."
--JOURNAL OF MATHEMATICAL PSYCHOLOGY, March 2000

From the Back Cover
The Theory of Rank Tests (developed in 1967) has been the precursor of a unified and theoretically motivated treatise of the basic theory of tests based on ranks of the sample observations, having exact distribution-freeness under the hypotheses of invariance, local optimality properties, computational simplicities, and general asymptotic properties in a broader setup.

For more than 25 years, before the book went out of print, this text has raised a generation of statisticians in cultivating their theoretical
research in this fertile area, as well as, in using these tools in their application oriented research. The theory of Rank Tests has probably the highest citation in statistical inference Citation Indexes.

The present edition not only aims to revive this classical text by updating the findings but also in incorporating several other important areas
those were either not properly developed before 1965 or have gone through an evolutionary development during the past 30 years. In that way,
the current venture aims to fulfill the need for all these academic as well as professional statisticians who want to pursue nonparametrics in their academic projects, consulation and applied research works. It is a unique blending of theory with fruitful applications in mind.

About the Author
Zbynek Šidák was Chairman, Department of Probability and Statistics at the Mathematical Institute, Academy of Sciences, Czech Republic. He is now the principal research worker there. He has worked at various American universities as well. For 30 years, he was Editor of the journal Applications of Mathematics. His interests in statistics were rank tests, multivariate and cluster analysis, ranking and selection procedures, and Markov chains.

Pranab K. Sen is Cary C. Boshamer Professor of Biostatistics and Statistics at the University of North Carolina, and is a Fellow of the Institute of Mathematical Statistics and of the American Statistical Association. He is also an elected member of the International Statistical Institute.Prenab K. Sen is author or co-author of multiple volumes in Mathematical Statistics, Probability Theory and Biostatistics, and has published extensively in nonparametrics, multivariate and sequential analysis, and reliability and survival analysis.

Jaroslav Hájek was Professor and Chairman, Department of Probability and Statistics at Charles University, Prague, Czech Republic, and also a Visiting Professor at several American universities. His contributions to statistics are very profound, especially in rank test theory, survey sampling, estimation theory, and statistics in random processes. He died in 1974 at the age of 48.