Response Modeling Methodology: Empirical Modeling For Engineering And Science
by
Haim Shore
Book Details
Format
Hardback or Cased Book
ISBN-10
9812561021
ISBN-13
9789812561022
Publisher
World Scientific Publishing Co Pte Ltd
Imprint
World Scientific Publishing Co Pte Ltd
Country of Manufacture
SG
Country of Publication
GB
Publication Date
Apr 26th, 2005
Print length
460 Pages
Weight
764 grams
Dimensions
23.20 x 15.80 x 3.00 cms
Product Classification:
Engineering: general
Ksh 25,400.00
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This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements. In addition, he explains the motivation for the development of the new methodology, introduces in detail the new approach and its estimation procedures, and shows how it may provide an excellent alternative to current approaches for empirical modeling (like Generalized Linear Modeling, GLM). The book also demonstrates that a myriad of current relational models, developed independently in various engineering and scientific disciplines, are in fact special cases of the RMM model, and so are many current statistical distributions, transformations and approximations.
This book introduces a new approach, denoted RMM, for an empirical modeling of a response variation, relating to both systematic variation and random variation. In the book, the developer of RMM discusses the required properties of empirical modeling and evaluates how current approaches conform to these requirements. In addition, he explains the motivation for the development of the new methodology, introduces in detail the new approach and its estimation procedures, and shows how it may provide an excellent alternative to current approaches for empirical modeling (like Generalized Linear Modeling, GLM). The book also demonstrates that a myriad of current relational models, developed independently in various engineering and scientific disciplines, are in fact special cases of the RMM model, and so are many current statistical distributions, transformations and approximations.
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