Expected distances and goodness-of-fit for the asymmetric Laplace distribution is used
- to compute its statistic and p-value by calling function statcompute;
- to compute its quantiles by calling function compquant or many.crit;
- to compute its power by calling function powcomp.fast or powcomp.easy.
Pierre Lafaye de Micheaux, Viet Anh Tran (2016). PoweR: A Reproducible Research Tool to Ease Monte Carlo Power Simulation Studies for Goodness-of-fit Tests in R. Journal of Statistical Software, 69(3), 1--42. doi:10.18637/jss.v069.i03
Rizzo, M. L., Haman, J. T. 2016. Expected distances and goodness-of-fit for the asymmetric Laplace distribution. Statist. Probab. Lett., 117, 158-164.
See Laplace.tests for other goodness-of-fit tests
for the Laplace distribution.