The remainder of the book is devoted to model and variable selection, Monte Carlo methods, nonparametric curve estimation, and prediction, classification, and machine learning topics. The necessary background material is included in an appendix. Using the tools and methods developed in this textbook, students will be ready for advanced research in modern statistics.
Numerous examples illustrate statistical modeling and inference concepts while end-of-chapter problems reinforce elementary concepts and introduce important new topics. As in Volume I, measure theory is not required for understanding. Check out Volume I for fundamental, classical statistical concepts leading to the material in this volume.
Mathematical Statistics: Basic Ideas and Selected Topics, Volume I, Second Edition
This item has been added to your basket View basket Checkout. The solutions to exercises for Volume II are included in the back of the book. Furthermore, these modern topics are considered with greater depth and sophistication than is usual in a general purpose text. And throughout its pages the book does a good job of linking the mathematical developments to major examples. The choice of topics and examples, along with the depth of coverage are the most attractive features of this volume. Keener, University of Michigan. Added to basket. Statistics Explained.
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Fifty Challenging Problems in Probability with Solutions. Frederick Mosteller.
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Mathematical Statistics: Basic Ideas and Selected Topics, Vol I
Ya'acov Ritov University of Michigan Verified email at umich. Shahed Hossain icddr,b Verified email at icddrb. Senior Scientist, Department of Statistics. University of Wisconsin, Madison. Verified email at stat. Articles Cited by Co-authors. Mathematical statistics: basic ideas and selected topics. Journal of the american statistical association 76 , , Journal of the American Statistical Association 83 , , The Annals of Mathematical Statistics 40 4 , , Articles 1—20 Show more.
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