Statistical modeling is a critical tool in scientific research. Statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems and to control such systems, as well as to make reliable predictions in various natural and social science fields. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. We hope that this book will be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science.
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Vendeur : -OnTimeBooks-, Phoenix, AZ, Etats-Unis
Etat : good. A copy that has been read, remains in good condition. All pages are intact, and the cover is intact. The spine and cover show signs of wear. Pages can include notes and highlighting and show signs of wear, and the copy can include "From the library of" labels or previous owner inscriptions. 100% GUARANTEE! Shipped with delivery confirmation, if you're not satisfied with purchase please return item! Ships via media mail. N° de réf. du vendeur OTV.0387718869.G
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Vendeur : Books Puddle, Woodside, NY, Etats-Unis
Etat : New. pp. 292. N° de réf. du vendeur 26285780
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Vendeur : Majestic Books, Hounslow, Royaume-Uni
Etat : New. pp. 292 52:B&W 6.14 x 9.21in or 234 x 156mm (Royal 8vo) Case Laminate on White w/Gloss Lam. N° de réf. du vendeur 7594891
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Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Statistical modeling is a critical tool in scientific research. This book provides comprehensive explanations of the concepts and philosophy of statistical modeling, together with a wide range of practical and numerical examples. The authors expect this work to be of great value not just to statisticians but also to researchers and practitioners in various fields of research such as information science, computer science, engineering, bioinformatics, economics, marketing and environmental science. It's a crucial area of study, as statistical models are used to understand phenomena with uncertainty and to determine the structure of complex systems. They're also used to control such systems, as well as to make reliable predictions in various natural and social science fields. 292 pp. Englisch. N° de réf. du vendeur 9780387718866
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Vendeur : moluna, Greven, Allemagne
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. With the development of modeling techniques, it has been required to construct model selection criteria, relaxing the assumptions imposed AIC and BICStatistical modeling is a critical tool in scientific research. This book provides comprehensi. N° de réf. du vendeur 5910660
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : New. N° de réf. du vendeur 5212875-n
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Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 5212875
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Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Etat : New. In English. N° de réf. du vendeur ria9780387718866_new
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Vendeur : California Books, Miami, FL, Etats-Unis
Etat : New. N° de réf. du vendeur I-9780387718866
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Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - The Akaike information criterion (AIC) derived as an estimator of the Kullback-Leibler information discrepancy provides a useful tool for evaluating statistical models, and numerous successful applications of the AIC have been reported in various fields of natural sciences, social sciences and engineering.One of the main objectives of this book is to provide comprehensive explanations of the concepts and derivations of the AIC and related criteria, including Schwarz's Bayesian information criterion (BIC), together with a wide range of practical examples of model selection and evaluation criteria. A secondary objective is to provide a theoretical basis for the analysis and extension of information criteria via a statistical functional approach. A generalized information criterion (GIC) and a bootstrap information criterion are presented, which provide unified tools for modeling and model evaluation for a diverse range of models, including various types of nonlinear models and model estimation procedures such as robust estimation, the maximum penalized likelihood method and a Bayesian approach. N° de réf. du vendeur 9780387718866
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