Computer Program for Krishnaiah’s Finite Intersection Tests for Multiple Comparisons of Mean Vectors

C. M. Cox, C. Fang and R. M. Boudreau
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C. M. Cox: University of Pittsburgh
C. Fang: University of Pittsburgh
R. M. Boudreau: University of Pittsburgh

A chapter in Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, 1981, pp 299-303 from Springer

Abstract: Abstract The program FIT performs Krishnaiah’s finite intersection test procedure on the mean vectors from k multivariate populations. The test procedure is valid under the following assumptions: a) the k populations are distributed as multivariate normal, b) the covariance matrices of the k populations are equal. We can perform twosided or one-sided tests. The common covariance matrix, ∑ = (σij) may be unknown or known. When ∑ is unknown, the test statistics are distributed as multivariate F or multivariate t for the two-sided test or the one-sided test respectively. In the case when ∑ is known, then the test statistics are distributed as multivariate chi-square or multivariate normal for the two-sided test or the one-sided test respectively. The program FIT computes suitable bounds on the required percentage points of these distributions.

Keywords: finite intersection test; multiple comparisons of mean vectors; linear combinations; multivariate F; multivariate t; multivariate chi-square; multivariate normal distributions (search for similar items in EconPapers)
Date: 1981
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DOI: 10.1007/978-1-4613-9464-8_44

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