Electronic Resource

A Multiple-testing approach to the multivariate Behrens-Fisher problem : with simulations and examples in SAS®

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In statistics, the Behrens–Fisher problem is the problem of interval estimation and hypothesis testing concerning the difference between the means of two normally distributed populations when the variances of the two populations are not assumed to be equal, based on two independent samples. In his 1935 paper, Fisher outlined an approach to the Behrens-Fisher problem. Since high-speed computers were not available in Fisher’s time, this approach was not implementable and was soon forgotten. Fortunately, now that high-speed computers are available, this approach can easily be implemented using just a desktop or a laptop computer. Furthermore, Fisher’s approach was proposed for univariate samples. But this approach can also be generalized to the multivariate case. In this monograph, we present the solution to the afore-mentioned multivariate generalization of the Behrens-Fisher problem. We start out by presenting a test of multivariate normality, proceed to test(s) of equality of covariance matrices, and end with our solution to the multivariate Behrens-Fisher problem. All methods proposed in this monograph will be include both the randomly-incomplete-data case as well as the complete-data case. Moreover, all methods considered in this monograph will be tested using both simulations and examples.

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Ketersediaan

Informasi Detail

Judul Seri

SpringerBriefs in Statistics

No. Panggil

E552

Penerbit

New York : Springer New York., 2013

Deskripsi Fisik

v, 55hlm.

Bahasa

English

ISBN/ISSN

9781461464433

Klasifikasi

NONE

Tipe Isi

-

Tipe Media

computer

Tipe Pembawa

online resource

Edisi

1

Subjek

Statistik
Analisis Multivariat
Matriks Kovarians

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Tejas Desai

Versi lain/terkait

Lampiran Berkas

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