On an F-type statistic for testing one-sided hypotheses and computation of chi-bar-squared weights

Mervyn J. Silvapulle

Statistics & Probability Letters, 1996, vol. 28, issue 2, 137-141

Abstract: A natural generalization of the well-known F-statistic is introduced for testing one-sided hypotheses. The exact finite sample null distribution of this statistic is shown to be a weighted sum of F-distributions. This resembles the large sample null distribution of the likelihood ratio statistic, a chi-bar squared distribution, which is a weighted sum of [chi]2 distributions. It turns out that the weights in these two distributions are identical; this is an important feature because we can use essentially the same computer programs for computing the p-values for the F- and the likelihood ratio statistics. A general stimulation procedure for computing the chi-bar-squared weights when the linear inequalities in the alternative hypothesis are not independent is introduced

Keywords: Chi-bar-squared; distributions; Dependent; inequality; constraints; Nonstandard; conditions; One-sided; F-test (search for similar items in EconPapers)
Date: 1996
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Citations: View citations in EconPapers (4)

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