Multinomial Goodness-of-Fit: Large-Sample Tests with Survey Design Correction and Exact Tests for Small Samples

Fast large-sample goodness-of-fit tests for copulas

Goodness-of-fit tests are a fundamental element in the copula-based modeling of multivariate continuous distributions. Among the different procedures proposed in the literature, recent large scale simulations suggest that one of the most powerful tests is based on the empirical process comparing the empirical copula with a parametric estimate of the copula derived under the null hypothesis. As ...

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...

Improved Power in Multinomial Goodness-of-fit Tests

The Pearson’s chi-square and the log likelihood ratio chi-square statistics are fundamental tools in goodnessof-fit testing. Cressie and Read (1984) constructed a general family of divergences which includes both statistics as special cases. This family is indexed by a single parameter, and divergences at either end of the scale are more powerful against alternatives of one type while being rat...

On Goodness-of-fit Tests

Goodness-of-fit tests for Archimedean copulas in large dimensions

A goodness-of-fit test for exchangeable Archimedean copulas is presented. In a large-scale simulation study it is shown that the test performs well according to the error probability of the first kind and the power under several alternatives, especially in large dimensions. The proposed test is compared to other known tests for Archimedean copulas. In contrast to the latter, the former is simpl...