Smooth goodness-of-fit tests for composite hypothesis in hazard based models

Goodness-of-fit tests in mixed models

Mixed models, with both random and fixed effects, are most often estimated on the assumption that the random effects are normally distributed. In this paper we propose several formal tests of the hypothesis that the random effects and/or errors are normally distributed. Most of the proposed methods can be extended to generalized linear models where tests for non-normal distributions are of inte...

The Comparison Between Goodness of Fit Tests for Copula

‎Copula functions as a model can show the relationship between variables‎. ‎Appropriate copula function for a specific application is a function that shows the dependency between data in a best way‎. ‎Goodness of fit tests theoretically are the best way in selection of copula function‎. ‎Different ways of goodness of fit for copula exist‎. ‎In this paper we will examine the goodness of fit test...

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...

Goodness-of-fit Tests for high-dimensional Gaussian linear models

Let (Y, (Xi)1≤i≤p) be a real zero mean Gaussian vector and V be a subset of {1, . . . , p}. Suppose we are given n i.i.d. replications of this vector. We propose a new test for testing that Y is independent of (Xi)i∈{1,...p}\V conditionally to (Xi)i∈V against the general alternative that it is not. This procedure does not depend on any prior information on the covariance of X or the variance of...

Goodness-of-Fit Tests for Parametri Regression Models