Information and Complexity in Statistical Modeling (Paperback, Softcover reprint of hardcover 1st ed. 2007)


No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.


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Product Description

No statistical model is "true" or "false," "right" or "wrong"; the models just have varying performance, which can be assessed. The main theme in this book is to teach modeling based on the principle that the objective is to extract the information from data that can be learned with suggested classes of probability models. The intuitive and fundamental concepts of complexity, learnable information, and noise are formalized, which provides a firm information theoretic foundation for statistical modeling. Although the prerequisites include only basic probability calculus and statistics, a moderate level of mathematical proficiency would be beneficial.

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Product Details

General

Imprint

Springer-Verlag New York

Country of origin

United States

Series

Information Science and Statistics

Release date

November 2010

Availability

Expected to ship within 10 - 15 working days

First published

2007

Authors

Dimensions

235 x 155 x 8mm (L x W x T)

Format

Paperback

Pages

142

Edition

Softcover reprint of hardcover 1st ed. 2007

ISBN-13

978-1-4419-2267-0

Barcode

9781441922670

Categories

LSN

1-4419-2267-9



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