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Resampling Methods for Dependent Data (Springer Series in Statistics), by S. N. Lahiri
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By giving a detailed account of bootstrap methods and their properties for dependent data, this book provides illustrative numerical examples throughout. The book fills a gap in the literature covering research on re-sampling methods for dependent data that has witnessed vigorous growth over the last two decades but remains scattered in various statistics and econometrics journals. It can be used as a graduate level text and also as a research monograph for statisticians and econometricians.
- Sales Rank: #3070679 in Books
- Published on: 2003-08-07
- Original language: English
- Number of items: 1
- Dimensions: 9.21" h x .88" w x 6.14" l, 1.61 pounds
- Binding: Hardcover
- 374 pages
Review
From the reviews:
"This book contains a large amount of material on resampling methods for dependent data ??? . the book is self-contained and therefore can be used as a text for a graduate level course in resampling methods; at the same time, the book is a valuable reference book for researchers. ??? This is a thorough book going into much detail ??? . an excellent book on resampling methods for dependent data which has filled a long lasting gap in the statistical literature." (Efstathios Paparoditis, Sankhya: The Indian Journal of Statistics, Vol. 65 (4), 2003)
"I found this a useful book that organizes many scattered results in a reasonably concise form. The author states that this book has two main audiences, so the first five chapters are a pedantic introduction aimed at graduate students and the last seven a research monograph aimed at researchers in statistics and econometrics. ??? In summary, I learned quite a bit from reading this book and consider it a good reference book for the mathematically inclined." (D.J. Thomson, Short Book Reviews, Vol. 24 (2), 2004)
"Bootstrap methods have seen vigorous growth over the past twenty years, and the book by Lahiri is extremely timely in its appearance. ??? The first five chapters are written in textbook style and this part is aimed at a postgraduate student audience. ??? The second part of the book (chapters 6 ??? 12) is written in the form of a research monograph. It is therefore primarily aimed at researchers ??? . this is a well written book, containing a wealth of information ??? ." (Tertius de Wet, Newsletter of the South African StatisticalAssociation, June, 2004)
"This book is devoted to resampling methods for dependent data, which has been a fast developing area in about the last twenty years. ??? provides an introduction to the area of resampling methods for dependent data and also presents the latest results in the area with quite a long reference list. The first part of the book can be used as a textbook, while the second part, which focuses on the advanced results, can be really useful for researchers in statistics and econometrics." (M. Hu??kov??, Mathematical Reviews, 2004f)
From the reviews:
"This book contains a large amount of material on resampling methods for dependent data a ] . the book is self-contained and therefore can be used as a text for a graduate level course in resampling methods; at the same time, the book is a valuable reference book for researchers. a ] This is a thorough book going into much detail a ] . an excellent book on resampling methods for dependent data which has filled a long lasting gap in the statistical literature." (Efstathios Paparoditis, Sankhya: The Indian Journal of Statistics, Vol. 65 (4), 2003)
"I found this a useful book that organizes many scattered results in a reasonably concise form. The author states that this book has two main audiences, so the first five chapters are a pedantic introduction aimed at graduate students and the last seven a research monograph aimed at researchers in statistics and econometrics. a ] In summary, I learned quite a bit from reading this book and consider it a good reference book for the mathematically inclined." (D.J. Thomson, Short Book Reviews, Vol. 24 (2), 2004)
"Bootstrap methods have seen vigorous growth over the past twenty years, and the book by Lahiri is extremely timely in its appearance. a ] The first five chapters are written in textbook style and this part is aimed at a postgraduate student audience. a ] The second part of the book (chapters 6 a" 12) is written in the form of a research monograph. It is therefore primarily aimed at researchers a ] . this is a well written book, containing a wealth of information a ] ." (Tertius de Wet, Newsletter of the South African Statistical Association, June, 2004)
"This book is devoted to resampling methods fordependent data, which has been a fast developing area in about the last twenty years. a ] provides an introduction to the area of resampling methods for dependent data and also presents the latest results in the area with quite a long reference list. The first part of the book can be used as a textbook, while the second part, which focuses on the advanced results, can be really useful for researchers in statistics and econometrics." (M. HuAkovA, Mathematical Reviews, 2004f)
Most helpful customer reviews
32 of 33 people found the following review helpful.
first resampling book dedicated to dependent data
By Michael R. Chernick
Books on the bootstrap and other resampling methods with a strong theoretical basis haven't appeared since 1999. So in 2003 this was a very welcome addition to the texts on resampling. It begins with a very good review of the bootstrap in the independent case. Then it goes on to give a delailed and thorough account of the dependent data case. Other books Davison and Hinkley (1997) and Chernick (1999) covered bootstrapping for time series and regression. However Lahiri, covers the block bootstrap and other methods for other types of dependencies as well. Also Professor Lahiri has made his own significant contributions to the research in resampling for dependent data and covers that important work very clearly in this book. It is because of the current nature of the theoretical and applied results covered in this book that I have cited it quite heavily in the second edition of my book Chernick (2007) that was just published.
References
1. Davison, A. C. and Hinkley, D. V. (1997). "Bootstrap Methods and Their Applications", Cambridge University Press, Cambridge, UK.
2. Chernick, M. R. (1999). "Bootstrap Methods: A Practitioner's Guide", Wiley, New York.
3. Chernick, M. R. (2007). "Bootstrap Methods: A Guide for Researchers and Practitioners", 2nd Edition, Wiley, New York.
1 of 1 people found the following review helpful.
Excellent source for learning...a must-have book!
By Kedar Patel
First of all, I'm not a statistician. I'm an elect. engineer who needed to understand and employ resampling techniques for innovative research in my area. I started by scouring through published literature in journals and came across many of Prof. Lahiri's works. He is a recognized expert with many of his seminal papers cited by numerous times by his peers.
I then stumbled across this book. This book is the most comprehensive book I found on this subject. It covers almost all the main ideas that were developed in the last two decades. I believe it is exceptionally well written and more importantly well organized. He starts of by covering the basics and gradually moves the discussion to more advanced topics. He does so precisely in the manner in which a critical thought-process would lead.
My only suggestion for improvement in subsequent edition would be to provide a companion software (written in Matlab and/or R) to go along with many of the techniques discussed in the book. This would further aid the understanding as there is no better way to learn than implementing the algorithms.
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