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Опубликовано на портале: 24-06-2004
William Jay Conover, Mark E. Johnson, Myrle M. Johnson Technometrics. 1981.  Vol. 23. No. 4. P. 351-361. 
Many of the existing parametric and nonparametric tests for homogeneity of variances, and some variations of these tests, are examined in this paper. Comparisons are made under the null hypothesis (for robustness) and under the alternative (for power). Monte Carlo simulations of various symmetric and asymmetric distributions, for various sample sizes, reveal a few tests that are robust and have good power. These tests are further compared using data from outer continental shelf bidding on oil and gas leases.
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Опубликовано на портале: 01-07-2004
Michael A. Stephens, Pedro Puig Technometrics. 2000.  Vol. 42. No. 4. P. 417-424. 
Tests are given for Laplace or double exponential distribution. The test statistics are based on the empirical distribution function and include and the families of Cramer-von Mises and Kolmogorov-Smirnov. Asymptotic theory is given, and asymptotic points are calculated, for the Cramer-von Mises family, and Monte Carlo points for finite samples are given for all the statistics. Power studies suggest that the Watson statistic is the most powerful for the common problem of testing Laplace against other symmetric distributions. An application of the Laplace distribution is in LAD (or L1) regression. This is also discussed in the article, with two examples.
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