Theory of Rank TestsBy
- Zbynek Sidak, Mathematical Institute Academy of Sciences, Czech Republic
- Pranab Sen, University of North Carolina, Chapel Hill, U.S.A.
- Jaroslav Hajek
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.
Graduate students in mathematical sciences (statistics, applied statistics, and biostatistics), academics, professional statisticians, and mathematicians.
Hardbound, 435 Pages
Published: March 1999
Imprint: Academic Press
s book is an updated second edition of the famous and outstanding textbook of Hájek and idák. The statistical community is grateful to idák 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
- Introduction and Coverage. Preliminaries. Elementary Theory of Rank Tests. Selected Rank Tests. Computation of Null Exact Distributions. Limiting Null Distributions. Limiting Non-Null Distributions. Asymptotic Optimality and Efficiency. Rank Estimates and Asymptotic Linearity.