RESPONSE MODELING METHODOLOGY: EMPIRICAL MODELING FOR ENGINEERING AND SCIENCE (Q

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eBay item number:405551568172
Last updated on Jun 21, 2025 18:23:10 PDTView all revisionsView all revisions

Item specifics

Condition
Very Good: A book that does not look new and has been read but is in excellent condition. No obvious ...
ISBN
9789812561022
Publication Year
2005
Series
Series on Quality, Reliability and Engineering Statistics
Type
Textbook
Format
Hardcover
Language
English
Subject Area
Technology & Engineering, Business & Economics
Publication Name
Response Modeling Methodology (Rmm) : Empirical Modeling for Engineering and Science
Author
Haim Shore
Publisher
World Industries Scientific Publishing Co Pte LTD
Subject
Industrial Engineering, Production & Operations Management, Quality Control
Number of Pages
460 Pages
Category

About this product

Product Identifiers

Publisher
World Industries Scientific Publishing Co Pte LTD
ISBN-10
9812561021
ISBN-13
9789812561022
eBay Product ID (ePID)
44588032

Product Key Features

Number of Pages
460 Pages
Publication Name
Response Modeling Methodology (Rmm) : Empirical Modeling for Engineering and Science
Language
English
Subject
Industrial Engineering, Production & Operations Management, Quality Control
Publication Year
2005
Type
Textbook
Subject Area
Technology & Engineering, Business & Economics
Author
Haim Shore
Series
Series on Quality, Reliability and Engineering Statistics
Format
Hardcover

Additional Product Features

Intended Audience
Scholarly & Professional
LCCN
2005-296212
Dewey Edition
22
Series Volume Number
Vol. 8
Illustrated
Yes
Dewey Decimal
620/.00452
Synopsis
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.
LC Classification Number
TA169.S53 2005

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