Boundary-free kernel-smoothed goodness-of-fit tests for data on general interval

Goodness of Fit Tests Based on Kernel Density Estimators

The paper is devoted to goodness of fit tests based on probability density estimates generated by kernel functions. The test statistic is considered in the form of maximum of the normalized deviation of the estimate from its expected value or a hypothesized distribution density function. A comparative Monte Carlo power study of the investigated criterion is provided. Simulation results show tha...

Goodness-of-fit Tests Based on the Kernel Density Estimator

Given an i.i.d. sample drawn from a density f on the real line, the problem of testing whether f is in a given class of densities is considered. Testing procedures constructed on the basis of minimizing the L1-distance between a kernel density estimate and any density in the hypothesized class are investigated. General non-asymptotic bounds are derived for the power of the test. It is shown tha...

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 Goodness-of-fit Tests

Distribution Free Goodness-of-fit Tests for Linear Processes

This article proposes goodness-of-...t tests based on a linear transformation of Barlett’s Tp¡process, which converges weakly to the standard Brownian motion under the null hypothesis, in the lines suggested by Khmaladze (1981). We show that the proposed test is capable to detect contiguous alternatives converging to the null at rate n¡1=2: A Monte Carlo study illustrates the performance of the...