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A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem: with Simulations and Examples in SAS® (SpringerBriefs in Statistics) - Tapa blanda
Sinopsis
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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Tejas A. Desai is Assistant Professor at The Adani Institute of Infrastructure Management
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A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem: with Simulations and Examples in SAS® (SpringerBriefs in Statistics)
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Multiple-testing Approach to the Multivariate Behrens-fisher Problem : With Simulations and Examples in Sas®
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A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem (Paperback)
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Paperback. Condición: new. Paperback. In statistics, the BehrensFisher 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 Fishers 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, Fishers 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. In statistics, the BehrensFisher 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781461464426
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A Multiple-Testing Approach to the Multivariate Behrens-Fisher Problem: with Simulations and Examples in SAS® (SpringerBriefs in Statistics)
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