Overview
- 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
Part of the book series: Springer Optimization and Its Applications (SOIA, volume 54)
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Table of contents (6 chapters)
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Bibliographic Information
Book Title: Regression Analysis Under A Priori Parameter Restrictions
Authors: Pavel S. Knopov, Arnold S. Korkhin
Series Title: Springer Optimization and Its Applications
DOI: https://doi.org/10.1007/978-1-4614-0574-0
Publisher: Springer New York, NY
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Science+Business Media 2012
Hardcover ISBN: 978-1-4614-0573-3Published: 27 September 2011
Softcover ISBN: 978-1-4614-2955-5Published: 24 October 2013
eBook ISBN: 978-1-4614-0574-0Published: 28 September 2011
Series ISSN: 1931-6828
Series E-ISSN: 1931-6836
Edition Number: 1
Number of Pages: XIV, 234
Topics: Operations Research, Management Science, Statistical Theory and Methods, Probability Theory and Stochastic Processes