Marcin Mazur
Schedae Informaticae, Volume 27, 2018, pp. 59-68
https://doi.org/10.4467/20838476SI.18.005.10410We apply the optimal transport distance to construct two goodness of fit tests for (univariate) normality. The derived statistics are then compared with those used by the Shapiro-Wilk, the Anderson-Darling and the Cramer-von Mises tests. In particular, we preform Monte Carlo experiments, involving computations of the test power against some selected alternatives and wide range of sample sizes, which show efficiency of the obtained test procedures.
Marcin Mazur
Schedae Informaticae, Volume 27, 2018, pp. 69-79
https://doi.org/10.4467/20838476SI.18.006.10411In this paper we discuss a class of AutoEncoder based generative models based on one dimensional sliced approach. The idea is based on the reduction of the discrimination between samples to one-dimensional case.
Our experiments show that methods can be divided into two groups. First consists of methods which are a modification of standard normality tests, while the second is based on classical distances between samples.
It turns out that both groups are correct generative models, but the second one gives a slightly faster decrease rate of Frechet Inception Distance (FID).