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Essential Statistical Inference Theory and Methods

by Boos
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Current price ₹8,732.00
Original price ₹13,433.00
Original price ₹13,433.00
Original price ₹13,433.00
(-35%)
₹8,732.00
Current price ₹8,732.00

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Book cover type: Paperback
  • ISBN13: 9781489987938
  • Binding: Paperback
  • Subject: Mathematics and Statistics
  • Publisher: Springer Verlag
  • Publisher Imprint: Springer
  • Publication Date:
  • Pages: 568
  • Original Price: EUR 119.99
  • Language: English
  • Edition: N/A
  • Item Weight: 812 grams
  • BISAC Subject(s): Probability & Statistics / General and Mathematical & Statistical Software

From the Back Cover

​This book is for students and researchers who have had a first year graduate level mathematical statistics course. It covers classical likelihood, Bayesian, and permutation inference; an introduction to basic asymptotic distribution theory; and modern topics like M-estimation, the jackknife, and the bootstrap. R code is woven throughout the text, and there are a large number of examples and problems.

An important goal has been to make the topics accessible to a wide audience, with little overt reliance on measure theory. A typical semester course consists of Chapters 1-6 (likelihood-based estimation and testing, Bayesian inference, basic asymptotic results) plus selections from M-estimation and related testing and resampling methodology.

Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.

Dennis Boos and Len Stefanski are professors in the Department of Statistics at North Carolina State. Their research has been eclectic, often with a robustness angle, although Stefanski is also known for research concentrated on measurement error, including a co-authored book on non-linear measurement error models. In recent years the authors have jointly worked on variable selection methods.

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