Entropy Minimax Sourcebook: Multivariate statistical modeling

Entropy Minimax Sourcebook: Multivariate statistical modeling PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 752

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Entropy Minimax Sourcebook: Multivariate statistical modeling

Entropy Minimax Sourcebook: Multivariate statistical modeling PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 752

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Book Description


Entropy Minimax Sourcebook: Applications

Entropy Minimax Sourcebook: Applications PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 826

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Entropy Minimax Sourcebook: Computer implementation

Entropy Minimax Sourcebook: Computer implementation PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 272

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Entropy Minimax Sourcebook: Belief and behavior

Entropy Minimax Sourcebook: Belief and behavior PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 402

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Architecture of Systems Problem Solving

Architecture of Systems Problem Solving PDF Author: George J. Klir
Publisher: Springer Science & Business Media
ISBN: 1475711689
Category : Computers
Languages : en
Pages : 537

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Book Description
One criterion for classifying books is whether they are written for a single purpose or for multiple purposes. This book belongs to the category of multipurpose books, but one of its roles is predominant-it is primarily a textbook. As such, it can be used for a variety of courses at the first-year graduate or upper-division undergraduate level. A common characteristic of these courses is that they cover fundamental systems concepts, major categories of systems problems, and some selected methods for dealing with these problems at a rather general level. A unique feature of the book is that the concepts, problems, and methods are introduced in the context of an architectural formulation of an expert system referred to as the general systems problem solver or GSPS-whose aim is to provide users of all kinds with computer-based systems knowledge and methodology. The GSPS architecture, which is developed throughout the book, facilitates a framework that is conducive to a coherent, comprehensive, and pragmatic coverage of systems fundamentals--concepts, problems, and methods. A course that covers systems fundamentals is now offered not only in systems ~cience, information science, or systems engineering programs, but in many programs in other disciplines as well. Although the level of coverage for systems science or engineering students is surely different from that used for students in other disciplines, this book is designed to serve both of these needs.

Entropy Measures, Maximum Entropy Principle and Emerging Applications

Entropy Measures, Maximum Entropy Principle and Emerging Applications PDF Author: Karmeshu
Publisher: Springer
ISBN: 3540362126
Category : Technology & Engineering
Languages : en
Pages : 300

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Book Description
The last two decades have witnessed an enormous growth with regard to ap plications of information theoretic framework in areas of physical, biological, engineering and even social sciences. In particular, growth has been spectac ular in the field of information technology,soft computing,nonlinear systems and molecular biology. Claude Shannon in 1948 laid the foundation of the field of information theory in the context of communication theory. It is in deed remarkable that his framework is as relevant today as was when he 1 proposed it. Shannon died on Feb 24, 2001. Arun Netravali observes "As if assuming that inexpensive, high-speed processing would come to pass, Shan non figured out the upper limits on communication rates. First in telephone channels, then in optical communications, and now in wireless, Shannon has had the utmost value in defining the engineering limits we face". Shannon introduced the concept of entropy. The notable feature of the entropy frame work is that it enables quantification of uncertainty present in a system. In many realistic situations one is confronted only with partial or incomplete information in the form of moment, or bounds on these values etc. ; and it is then required to construct a probabilistic model from this partial information. In such situations, the principle of maximum entropy provides a rational ba sis for constructing a probabilistic model. It is thus necessary and important to keep track of advances in the applications of maximum entropy principle to ever expanding areas of knowledge.

Entropy Minimax Sourcebook: Order and time

Entropy Minimax Sourcebook: Order and time PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 160

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Entropy Minimax Sourcebook: Foundations of inductive reasoning

Entropy Minimax Sourcebook: Foundations of inductive reasoning PDF Author: Ronald Christensen
Publisher:
ISBN:
Category : Correlation (Statistics)
Languages : en
Pages : 386

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Multivariable Analysis

Multivariable Analysis PDF Author: Alvan R. Feinstein
Publisher: Yale University Press
ISBN: 0300062990
Category : Reference
Languages : en
Pages : 644

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Book Description
A physician with wide experience in both clinical work and research, Dr. Feinstein succeeds in demystifying arcane vocabulary and unfamiliar mathematics. His book is a roadmap taking the reader from the basics of univariate and bivariate statistics, through methods of converting information into data coded for computers, and on to multivariable statistics. Dr.

Facets of Systems Science

Facets of Systems Science PDF Author: George J. Klir
Publisher: Springer Science & Business Media
ISBN: 1489907181
Category : Business & Economics
Languages : en
Pages : 650

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Book Description
This book has a rather strange history. It began in Spring 1989, thirteen years after our Systems Science Department at SUNY -Binghamton was established, when I was asked by a group of students in our doctoral program to have a meeting with them. The spokesman of the group, Cliff Joslyn, opened our meeting by stating its purpose. I can closely paraphrase what he said: "We called this meeting to discuss with you, as Chairman of the Department, a fundamental problem with our systems science curriculum. In general, we consider it a good curriculum: we learn a lot of concepts, principles, and methodological tools, mathematical, computational, heuristic, which are fundamental to understanding and dealing with systems. And, yet, we learn virtually nothing about systems science itself. What is systems science? What are its historical roots? What are its aims? Where does it stand and where is it likely to go? These are pressing questions to us. After all, aren't we supposed to carry the systems science flag after we graduate from this program? We feel that a broad introductory course to systems science is urgently needed in the curriculum. Do you agree with this assessment?" The answer was obvious and, yet, not easy to give: "I agree, of course, but I do not see how the situation could be alleviated in the foreseeable future.