Description: Please refer to the section BELOW (and NOT ABOVE) this line for the product details - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - Title:Information And Complexity In Statistical ModelingISBN13:9781441922670ISBN10:1441922679Author:Rissanen, Jorma (Author)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 Inspired By Kolmogorov's Structure Function In The Algorithmic Theory Of Complexity, This Is Accomplished By Finding The Shortest Code Length, Called The Stochastic Complexity, With Which The Data Can Be Encoded When Advantage Is Taken Of The Models In A Suggested Class, Which Amounts To The Mdl (Minimum Description Length) Principle The Complexity, In Turn, Breaks Up Into The Shortest Code Length For The Optimal Model In A Set Of Models That Can Be Optimally Distinguished From The Given Data And The Rest, Which Defines Noise As The Incompressible Part In The Data Without Useful Information Such A View Of The Modeling Problem Permits A Unified Treatment Of Any Type Of Parameters, Their Number, And Even Their Structure Since Only Optimally Distinguished Models Are Worthy Of Testing, We Get A Logically Sound And Straightforward Treatment Of Hypothesis Testing, In Which For The First Time The Confidence In The Test Result Can Be Assessed Although The Prerequisites Include Only Basic Probability Calculus And Statistics, A Moderate Level Of Mathematical Proficiency Would Be Beneficial The Different And Logically Unassailable View Of Statistical Modelling Should Provide Excellent Grounds For Further Research And Suggest Topics For Graduate Students In All Fields Of Modern Engineering, Including And Not Restricted To Signal And Image Processing, Bioinformatics, Pattern Recognition, And Machine Learning To Mention Just A Few Binding:Paperback, PaperbackPublisher:SPRINGER NATUREPublication Date:2010-11-23Weight:0.49 lbsDimensions:0.33'' H x 9.21'' L x 6.14'' WNumber of Pages:142Language:English
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Book Title: Information And Complexity In Statistical Modeling
Item Length: 9.3in
Item Width: 6.1in
Author: Jorma Rissanen
Publication Name: Information and Complexity in Statistical Modeling
Format: Trade Paperback
Language: English
Publisher: Springer NY
Series: Information Science and Statistics Ser.
Publication Year: 2010
Type: Textbook
Item Weight: 16 Oz
Number of Pages: VIII, 142 Pages