Robust testing for superiority between two regression curves

Robust testing for superiority between two regression curves

where mj : R → R is a nonparametric smooth function and the error εj is independent of the covariate Xj. As is usual in a robust framework, we will assume that the errors εj are such that εj = σj Uj, where Uj has a symmetric distribution Gj(·) with scale 1, so that we are able to identify the error’s scale, σj. When second moments exist, as it is the case of the classical approach, these condit...

Testing for Superiority among Two Regression Curves

Robust tests for testing the parameters of a normal population

This article aims to provide a simple robust method to test the parameters of a normal population by using the new diagnostic tool called the “Forward Search” (FS) method. The most commonly used procedures to test the mean and variance of a normal distribution are Student’s t test and Chi-square test, respectively. These tests suffer from the presence of outliers. We introduce the FS version of...

Robust Testing between Two Asymmetric Distributions: a Simulation Study

In this paper a robust test statistic for testing between two income distributions is analysed. Victoria-Feser (1996) proposed a robust version of the classical test based on the comparison of the maximised likelihood functions for the two models (Cox 1961, 1962). She showed its robustness properties as well as other properties. She also proposed an algorithm for the computation of the robust C...

Robust testing in the logistic regression model