7 papers
Divergence-based robust inference under proportional hazards model for one-shot device life-test
N. Balakrishnan, E. Castilla, N. Martin +1
In this paper, we develop robust estimators and tests for one-shot device testing under proportional hazards assumption based on divergence measures. Through a detailed Monte Carlo…
Power divergence approach for one-shot device testing under competing risks
N. Balakrishnan, E. Castilla, N. Martin +1
Most work on one-shot devices assume that there is only one possible cause of device failure. However, in practice, it is often the case that the products under study can experienc…
A Robust Generalization of the Rao Test
Ayanendranath Basu, Abhik Ghosh, Nirian Martin +1
This paper presents new families of Rao-type test statistics based on the minimum density power divergence estimators which provide robust generalizations for testing simple and co…
Robust semiparametric inference for polytomous logistic regression with complex survey design
Elena Castilla, Abhik Ghosh, Nirian Martin +1
Analyzing polytomous response from a complex survey scheme, like stratified or cluster sampling is very crucial in several socio-economics applications. We present a class of minim…
A Robust Wald-type Test for Testing the Equality of Two Means from Log-Normal Samples
Ayanendranath Basu, Abhijit Mandal, Nirian Martin +1
The log-normal distribution is one of the most common distributions used for modeling skewed and positive data. It frequently arises in many disciplines of science, specially in th…
Robust Wald-type test in GLM with random design based on minimum density power divergence estimators
Ayanendranath Basu, Abhik Ghosh, Abhijit Mandal +2
We consider the problem of robust inference under the generalized linear model (GLM) with stochastic covariates. We derive the properties of the minimum density power divergence es…