Stochastic Complexity in Statistical Inquiry - Couverture souple

Couverture souple

ISBN 10 : 981020311X ISBN 13 : 9789810203115

Editeur : World Scientific Publishing Co Pte Ltd, 1989

Synopsis

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.

Détails de l'édition

• Éditeur: World Scientific Publishing Co Pte Ltd
• Date d'édition: 1989
• Langue: anglais
• ISBN 10: 981020311X
• ISBN 13: 9789810203115
• Reliure: Broché
• Nombre de pages: 250
• Éditeur: Rissanen Jorma
• Coordonnées du fabricant: non disponible
• Personne responsable: non disponible