Stochastic complexity statistical inquiry (11 résultats)
- Couverture rigide
Vendeur : Anybook.com, Lincoln, Royaume-UniAnybook.com
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion - Satisfaisant
EUR 25,27
EUR 15,89 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 1 disponible(s)
Etat : Good. Volume 15. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. Book contains pencil markings. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,500grams, ISBN:9789971508593….
- Couverture souple
Vendeur : California Books, Miami, FL, Etats-UnisCalifornia Books
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 47,29
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New.
- Autres images
Langue : anglais
Edité par World Scientific Publishing Co Pte Ltd, SG, 1989
- Couverture souple
Vendeur : Rarewaves.com USA, London, LONDO, Royaume-UniRarewaves.com USA
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 58,36
Frais de port gratuitsExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. 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.
- Couverture souple
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 61,04
EUR 11,69 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Paperback. Etat : Brand New. 250 pages. 6.00x0.52x9.00 inches. In Stock.
- Couverture rigide
Vendeur : California Books, Miami, FL, Etats-UnisCalifornia Books
Contacter le vendeurVendeur avec une évaluation de 4 étoilesEtat: Neuf
EUR 74,95
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New.
Langue : anglais
Edité par World Scientific Publishing Co Pte Ltd, SG, 1989
- Couverture souple
Vendeur : Rarewaves USA United, OSWEGO, IL, Etats-UnisRarewaves USA United
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 54,87
EUR 43,31 expéditionExpédition nationale : Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. 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.
- Couverture rigide
Vendeur : Revaluation Books, Exeter, Royaume-UniRevaluation Books
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 98,32
EUR 11,69 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : 2 disponible(s)
Hardcover. Etat : Brand New. 188 pages. 8.50x6.50x0.50 inches. In Stock.
- Autres images
- Couverture rigide
Vendeur : -OnTimeBooks-, Phoenix, AZ, Etats-Unis-OnTimeBooks-
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Occasion - Assez bon
EUR 114,14
Frais de port gratuitsExpédition nationale : Etats-UnisQuantité disponible : 1 disponible(s)
Etat : very_good. Gently read. May have name of previous ownership, or ex-library edition. Binding tight; spine straight and smooth, with no creasing; covers clean and crisp. Minimal signs of handling or shelving. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships…USPS Media Mail.
- Autres images
Langue : anglais
Edité par World Scientific Publishing Company Aug 1989, 1989
- Couverture souple
Vendeur : AHA-BUCH GmbH, Einbeck, AllemagneAHA-BUCH GmbH
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 63,00
EUR 65,00 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : 2 disponible(s)
Taschenbuch. Etat : Neu. Neuware - 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 assumption…s 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.
- Autres images
Langue : anglais
Edité par World Scientific Publishing Co Pte Ltd, SG, 1989
- Couverture souple
Vendeur : Rarewaves.com UK, London, Royaume-UniRarewaves.com UK
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 54,88
EUR 75,97 expéditionExpédition depuis Royaume-Uni vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Paperback. Etat : New. 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.
- Autres images
- Couverture souple
- impression à la demande
Vendeur : moluna, Greven, Allemagnemoluna
Contacter le vendeurVendeur avec une évaluation de 5 étoilesEtat: Neuf
EUR 55,00
EUR 48,99 expéditionExpédition depuis Allemagne vers Etats-UnisQuantité disponible : Plus de 20 disponibles
Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. KlappentextThis 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 compl…exity not only o.
