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ISBN: 9781461405740
This monograph focuses on the construction of regression models with linear and non-linear constrain inequalities from the theoretical point of view. In includes analysis of the propertie… Más…
ISBN: 9781461405740
*Regression Analysis Under A Priori Parameter Restrictions* / pdf eBook für 96.49 € / Aus dem Bereich: eBooks, Fachthemen & Wissenschaft, Mathematik Medien > Bücher nein eBook als pdf eBo… Más…
ISBN: 9781461405740
Regression Analysis Under A Priori Parameter Restrictions: ab 96.49 € eBooks > Fachthemen & Wissenschaft > Mathematik Springer-Verlag GmbH eBook als pdf, Springer-Verlag GmbH
2011, ISBN: 9781461405740
eBooks, eBook Download (PDF), 2012, [PU: Springer New York], Springer New York, 2011
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Detalles del libro - Regression Analysis Under A Priori Parameter Restrictions
EAN (ISBN-13): 9781461405740
ISBN (ISBN-10): 1461405742
Año de publicación: 2011
Editorial: Springer-Verlag GmbH
233 Páginas
Idioma: eng/Englisch
Libro en la base de datos desde 2012-10-09T09:05:49-05:00 (Mexico City)
Página de detalles modificada por última vez el 2023-11-16T06:28:33-06:00 (Mexico City)
ISBN/EAN: 1461405742
ISBN - escritura alterna:
1-4614-0574-2, 978-1-4614-0574-0
Mode alterno de escritura y términos de búsqueda relacionados:
Autor del libro: pavel, knop, arnold, allen
Título del libro: prior, analysis
Datos del la editorial
Autor: Pavel S. Knopov; Arnold S. Korkhin
Título: Springer Optimization and Its Applications; Regression Analysis Under A Priori Parameter Restrictions
Editorial: Springer; Springer US
234 Páginas
Año de publicación: 2011-09-28
New York; NY; US
Idioma: Inglés
96,29 € (DE)
99,00 € (AT)
118,00 CHF (CH)
Available
XIV, 234 p.
EA; E107; eBook; Nonbooks, PBS / Mathematik/Sonstiges; Unternehmensforschung; Verstehen; Computational Modeling; Inequality Restrictions; Predictive Regression; Statistical Regression; B; Operations Research, Management Science; Statistical Theory and Methods; Probability Theory; Mathematics and Statistics; Wahrscheinlichkeitsrechnung und Statistik; Stochastik; BC
Problems are described and studied in a clear, precise, and rigorous method and include: calculation of estimates for regression parameters, determination of their asymptotic properties and accuracy of estimation, point and interval prediction by the regression, parameters of which are estimatedunder inequality constraints. The authors’ approach lends itself to numerous applications in various practical problems, several of which are discussed in detail.Presents four central topics in stochastic optimization: calculation of parameter estimates, the asymptotic theory of estimates, estimation theory for small samples, and prediction theory Describes applications to practical problems from various areas of study including econometrics, clinical medicine, and several other experimental sciences Considers the problems of prediction by means of linear regression in the context of small samples
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