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Statistical Inference Based on Divergence Measures by Leandro Pardo

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Summary

Presents classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence with applications to multinomial and generation populations. On the basis of divergence measures, this book introduces minimum divergence estimators as well as divergence test statistics.

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Statistical Inference Based on Divergence Measures by Leandro Pardo

Presents classical problems of statistical inference, such as estimation and hypothesis testing, on the basis of measures of entropy and divergence with applications to multinomial and generation populations. On the basis of divergence measures, this book introduces minimum divergence estimators as well as divergence test statistics.

"There are a number of measures of divergence between distributionsDescribing them properly requires a very mathematically well-written book, which the author here provides … This book is a fine course text, and is beautifully produced. There are about four hundred references. Recommended."
-ISI Short Book Reviews

". . . suitable for a beginning graduate course on information theory based on statistical inference. This book will be a useful and important addition to the resources of practitioners and many others engaged information theory and statistics. Overall, this is an impressive book on information theory based statistical inference."

– Prasanna Sahoo, in Zentralblatt Math, 2008, Vol. 1120

Leandro Pardo
SKU Unavailable
ISBN 13 9781584886006
ISBN 10 1584886005
Title Statistical Inference Based on Divergence Measures
Author Leandro Pardo
Series Statistics: A Series Of Textbooks And Monographs
Condition Unavailable
Binding Type Hardback
Publisher CRC Press LLC
Year published 2005-10-10
Number of pages 512
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.