Discriminant functions for linear comparisons of means when covariance matrices are unequal

Situations exist, as in the biological example of discriminant analysis for natural hybridization, cited in the text, where (a) not all populations have equal variances, and (b) comparisions based on single degrees of freedom must be planned. This paper presents a statistical methodology of estimating discriminant functions for linear comparisons among k(<2) multivariate normal populations, and of testing their significance, when these populations have unequal covariance matrices.     

An Empirical Power Comparison of Three Tests of Exponentiality Under Mixture- and Outlier-Models

We present the results of an empirical power study of three prominent goodness-of-fit tests for exponentiality due to Shapiro and Wilk (1972), Durbin (1975), and Tiku (1980) by considering the mixture- and the outlier- exponential models as alternatives. This study is on similar lines as those of Dyer and Harbin (1981) and Balakrishnan (1983). We show that Tiku's test is on the whole considerably more powerful than the other two tests.