Power and Level Robustness of A Composite Hypothesis Testing under Independent Non-Homogeneous Data

10/01/2018
by   Abhik Ghosh, et al.
0

Robust tests of general composite hypothesis under non-identically distributed observations is always a challenge. Ghosh and Basu (2018, Statistica Sinica, 28, 1133--1155) have proposed a new class of test statistics for such problems based on the density power divergence, but their robustness with respect to the size and power are not studied in detail. This note fills this gap by providing a rigorous derivation of power and level influence functions of these tests to theoretically justify their robustness. Applications to the fixed-carrier linear regression model are also provided with empirical illustrations.

READ FULL TEXT
research
08/26/2019

A Robust Generalization of the Rao Test

This paper presents new families of Rao-type test statistics based on th...
research
03/31/2018

Robust Wald-type test in GLM with random design based on minimum density power divergence estimators

We consider the problem of robust inference under the important generali...
research
09/26/2020

Robust Hypothesis Testing and Model Selection for Parametric Proportional Hazard Regression Models

The semi-parametric Cox proportional hazards regression model has been w...
research
01/31/2023

Restricted distance-type Gaussian estimators based on density power divergence and their applications in hypothesis testing

Zhang (2019) presented a general estimation approach based on the Gaussi...
research
10/27/2019

Density Power Downweighting and Robust Inference: Some New Strategies

Preserving the robustness of the procedure has, at the present time, bec...
research
11/29/2021

The Fixed-b Limiting Distribution and the ERP of HAR Tests Under Nonstationarity

We show that the nonstandard limiting distribution of HAR test statistic...
research
01/13/2019

Asymptotics of an empirical bridge of a regression on induced order statistics

We propose a class of tests for linear regression on concomitants (induc...

Please sign up or login with your details

Forgot password? Click here to reset