2 research outputs found
A comprehensive empirical power comparison of univariate goodness-of-fit tests for the Laplace distribution
In this paper, we do a comprehensive survey of all univariate goodness-of-fit
tests that we could find in the literature for the Laplace distribution, which
amounts to a total of 45 different test statistics. After eliminating
duplicates and considering parameters that yield the best power for each test,
we obtain a total of 38 different test statistics. An empirical power
comparison study of unmatched size is then conducted using Monte Carlo
simulations, with 400 alternatives spanning over 20 families of distributions,
for various sample sizes and confidence levels. A discussion of the results
follows, where the best tests are selected for different classes of
alternatives. A similar study was conducted for the normal distribution in
Rom\~ao et al. (2010), although on a smaller scale. Our work improves
significantly on Puig & Stephens (2000), which was previously the best-known
reference of this kind for the Laplace distribution. All test statistics and
alternatives considered here are integrated within the PoweR package for the R
software.Comment: 37 pages, 1 figure, 20 table