This book is designed to bridge the gap between traditional textbooks in statistics and more advanced books that include the sophisticated nonparametric techniques. It covers topics in parametric and nonparametric large-sample estimation theory. The exposition is based on a collection of relatively simple statistical models. It gives a thorough mathematical analysis for each of them with all the rigorous proofs and explanations. The book also includes a number of helpful exercises. Prerequisites for the book include senior undergraduate/beginning graduate-level courses in probability and statistics.

About the Author
Alexander Korostelev Wayne State University, Detroit, MI, USA

Olga Korosteleva, California State University, Long Beach, CA, USA

Reviews
This is a well written book and should be of great interest to advanced graduate students/researchers in mathematical statistics. The material is presented with great clarity by using simple models as opposed to complex ones. ... Overall it should be of great value to advanced graduate students and researchers in theoretical statistics. The book can be recommended for libraries on campuses with a graduate program in statistics." - Mathematical Reviews



Book Information
ISBN 9780821852835
Author Alexander Korostelev
Format Hardback
Page Count 246
Imprint American Mathematical Society
Publisher American Mathematical Society
Weight(grams) 620g