Stochastic Complexity In Statistical Inquiry - Jorma Rissanen - 書籍 - World Scientific Publishing Co Pte Ltd - 9789810203115 - 1989年8月1日
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Stochastic Complexity In Statistical Inquiry

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発送予定日 年9月21日 - 年10月7日
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This book describes how model selection and statistical inference can be founded on the shortest code length for the observed data, called the stochastic complexity. This generalization of the algorithmic complexity not only offers an objective view of statistics, where no prejudiced assumptions of 'true' data generating distributions are needed, but it also in one stroke leads to calculable expressions in a range of situations of practical interest and links very closely with mainstream statistical theory. The search for the smallest stochastic complexity extends the classical maximum likelihood technique to a new global one, in which models can be compared regardless of their numbers of parameters. The result is a natural and far reaching extension of the traditional theory of estimation, where the Fisher information is replaced by the stochastic complexity and the Cramer-Rao inequality by an extension of the Shannon-Kullback inequality. Ideas are illustrated with applications from parametric and non-parametric regression, density and spectrum estimation, time series, hypothesis testing, contingency tables, and data compression.

メディア 書籍     Paperback Book   (ソフトカバーで背表紙を接着した本)
リリース済み 1989年8月1日
ISBN13 9789810203115
出版社 World Scientific Publishing Co Pte Ltd
ページ数 188
寸法 150 × 220 × 10 mm   ·   349 g
言語 英語  

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