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

In: Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface

Author

Listed:
  • C. M. Cox

    (University of Pittsburgh)

  • C. Fang

    (University of Pittsburgh)

  • R. M. Boudreau

    (University of Pittsburgh)

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.

Suggested Citation

  • C. M. Cox & C. Fang & R. M. Boudreau, 1981. "Computer Program for Krishnaiah’s Finite Intersection Tests for Multiple Comparisons of Mean Vectors," Springer Books, in: William F. Eddy (ed.), Computer Science and Statistics: Proceedings of the 13th Symposium on the Interface, pages 299-303, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4613-9464-8_44
    DOI: 10.1007/978-1-4613-9464-8_44
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