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Asymptotic Matrix Methods

 

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  • Product Description
 

The exact distributions of multivariate statistics used for the inference in multivariate analysis are usually not known or quite difficult to handle. The topic of this book belongs to the area of approximation of unknown distributions through classical distributions and to the related estimation problems. The methods used here are based on concepts of matrix algebra like the Kronecker product, the vec-operator and the matrix derivative. The multivariate normal distribution and the class of elliptical distributions are examined. The asymptotic variance of the sample correlation coefficient is calculated using approximate linearization. Some applications of the asymptotic distribution of the sample correlation coefficient are considered for populations with different distributions. The main term of the bias of the shape parameter of the asymmetric normal distribution and the Läuter's F-statistic was found using the Taylor expansion. Simulation experiments are described and the results of the simulation study are presented beside derivation of theoretical results.

Product Specifications
SKU :COC93864
AuthorOlga Dunajeva
LanguageEnglish
BindingPaperback
Number of Pages104
Publishing Year2011-12-08T00:00:00.000
ISBN978-3846599822
Edition1 st
Book TypeStochastics
Country of ManufactureIndia
Product BrandLAP LAMBERT Academic Publishing
Product Packaging InfoBox
In The Box1 Piece
Product First Available On ClickOnCare.com2015-08-14 00:00:00
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