A Robust Asymptotic Testing Model

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...

Asymptotic Robust Hypothesis Testing Based on Moment Classes

A robust hypothesis testing framework is introduced in which candidate hypotheses are characterized by moment classes. It is shown that there exists a test sequence that is asymptotically optimal in the min-max sense, and that it is expressed as a comparison of a log-linear combination of the constraint functions to a pre-determined threshold. Algorithms are described to compute the optimal tes...

Asymptotic Controllability and Robust Asymptotic Stabilizability

This paper deals with asymptotically controllable systems for which there exists no smooth stabilizing state feedback. To investigate the robustness asymptotic stabilization property, a new class of hybrid feedbacks (with a continuous component and a discrete one) is introduced: the hybrid patchy feedbacks. The notion of solutions is a generalization of π-solutions and Euler solutions. It is pr...

Robust testing in the logistic regression model

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...