Unbiased Estimators and their Applications: Volume 2: Multivariate Case by V.G. VoinovUnbiased Estimators and their Applications: Volume 2: Multivariate Case by V.G. Voinov

Unbiased Estimators and their Applications: Volume 2: Multivariate Case

byV.G. Voinov, M.S. Nikulin

Paperback | December 8, 2010

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This volume is a continuation ofUnbiased Estimators and TheirApplications, Vol. I: Univariate Case.It contains problems of parametric point estimation for multivariate probability distributions emphasizing problems of unbiased estimation. The volume consists of four chapters dealing, respectively, with some basic properties of multivariate continuous and discrete distributions, the general theory of point estimation in multivariate case, techniques for constructing unbiased estimators and applications of unbiased estimation theory in the multivariate case. These chapters contain numerous examples, many applications and are followed by a comprehensive Appendix which classifies and lists, in the form of tables, all known results relating to unbiased estimators of parameter functions for multivariate distributions.
Audience:This volume will serve as a handbook on point unbiased estimation for researchers whose work involves statistics. It can also be recommended as a supplementary text for undergraduate and graduate students.
Title:Unbiased Estimators and their Applications: Volume 2: Multivariate CaseFormat:PaperbackDimensions:262 pages, 24 × 16 × 0.01 inPublished:December 8, 2010Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:9048146763

ISBN - 13:9789048146765

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Table of Contents

Preface.1.Basic Remarks on Multivariate Probability Distributions.2.Elements of the Theory of Point Statistical Estimation in the Multivariate Case.3.Techniques for Constructing Unbiased Estimators.4.Applications of Unbiased Estimators.Appendix 1.Tables of Unbiased Estimators.Appendix 2.On Evaluating Some Multivariable Integrals.Appendix 3.Partitions and Some Multivariable Statistical Problems. References. Subject Index. Author Index.