Pseudosolution of Linear Functional Equations / Mathematics and Its Applications Bd.576 (PDF)

Name: Pseudosolution of Linear Functional Equations / Mathematics and Its Applications Bd.576
Brand: Springer-Verlag GmbH
SKU: 29545431
Price: 54.99 EUR
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Parameters Estimation of Linear Functional Relationships (Sprache: Englisch)

Autor: Alexander S. Mechenov

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Pseudosolution of Linear Functional Equations / Mathematics and Its Applications Bd.576, Alexander S. Mechenov

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This book presents the author's new method of two-stage maximization of likelihood function, which helps to solve a series of non-solving before the well-posed and ill-posed problems of pseudosolution computing systems of linear algebraic equations (or, in statistical terminology, parameters' estimators of functional relationships) and linear integral equations in the presence of deterministic and random errors in the initial data. This book, for the first time, presents a solution of the problem of reciprocal influence of passive errors of regressors and of active errors of predictors by computing point estimators of functional relationships.

Audience

This book is intended for students, postgraduate students, scientists, and other researchers on handling economical and technical data. The book is especially intended for those who constantly use regression analysis in their own research and for those who create the mathematical software for computers.

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Bibliographische Angaben

Autor: Alexander S. Mechenov
2005, 2005, 238 Seiten, Englisch
Verlag: Springer-Verlag GmbH
ISBN-10: 0387245065
ISBN-13: 9780387245065
Erscheinungsdatum: 25.07.2005

Abhängig von Bildschirmgröße und eingestellter Schriftgröße kann die Seitenzahl auf Ihrem Lesegerät variieren.

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From the reviews of the first edition:

"This book presents a method of two-stage maximization of a likelihood function, which helps to solve a series of non-solved before well-posed and ill-posed problems of pseudosolution computing systems of linear algebraic equations … . This book is intended for students, postgraduate students, scientists, and other researchers handling economical and technical data. It is especially intended for those who constantly use regression analysis in their own research and for those who create mathematical software for computers." (Yuehua Wu, Zentralblatt MATH, Vol. 1077, 2006)

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