Inferences on the ratio of two generalized variances: independent and correlated cases

Ali Jafari ()

Statistical Methods & Applications, 2012, vol. 21, issue 3, 297-314

Abstract: Statistical inferences about the dispersion of multivariate population are determined by generalized variance. In this article, we consider constructing a confidence interval and testing the hypotheses about the ratio of two independent generalized variances, and the ratio of two dependent generalized variances in two multivariate normal populations. In the case of independence, we first propose a computational approach and then obtain an approximate approach. In the case of dependence, we give an approach using the concepts of generalized confidence interval and generalized p value. In each case, simulation studies are performed for comparing the methods and we find satisfactory results. Practical examples are given for each approach. Copyright Springer-Verlag 2012

Keywords: Cholesky decomposition; Coverage probability; Generalized confidence interval; Generalized p value; Monte Carlo simulation (search for similar items in EconPapers)
Date: 2012
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10260-012-0191-6

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