Multivariate goodness-of-fit tests based on Wasserstein distance

Tests of Goodness of Fit Based on the L2-wasserstein Distance

Given P1 and P2 in the set of probabilities on the line with nite second order moment, P2(<); the L2-Wasserstein distance between P1 and P2, is deened as the lowest L2-distance between random variables with these distribution laws. When P 2 P2(<); has variance 2 0 ; and H is a location and scale family also in P2(<); the ratio (2 0) ?1 infQ2H W 2 (P; Q) does not depend on location or scale chan...

On the Canonical-Based Goodness-of-fit Tests for Multivariate Skew-Normality

It is well-known that the skew-normal distribution can provide an alternative model to the normal distribution for analyzing asymmetric data. The aim of this paper is to propose two goodness-of-fit tests for assessing whether a sample comes from a multivariate skew-normal (MSN) distribution. We address the problem of multivariate skew-normality goodness-of-fit based on the empirical Laplace tra...

On Goodness-of-fit Tests

Goodness-of-Fit Tests for Copulas of Multivariate Time Series

In this paper, we study the asymptotic behavior of the sequential empirical process and the sequential empirical copula process, both constructed from residuals of multivariate stochastic volatility models. Applications for the detection of structural changes and specification tests of the distribution of innovations are discussed. It is also shown that if the stochastic volatility matrices are...

An Updated Review of Goodness of Fit Tests Based on Entropy

Different approaches to goodness of fit (GOF) testing are proposed. This survey intends to present the developments on Goodness of Fit based on entropy during the last 50 years, from the very first origins until the most recent advances for different data and models. Goodness of fit tests based on Shannon entropy was started by Vasicek in 1976 and were continued by many authors. In this paper, ...