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20112022
most citedOn regularization methods based on Rényi's pseudodistances for sparse high-dimensional linear regression models

3 citations · 4 across the 7 of their papers we have counts for

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stat.ME20201 cited

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

Amarnath Nandy, Abhik Ghosh, Ayanendranath Basu +1

The semi-parametric Cox proportional hazards regression model has been widely used for many years in several applied sciences. However, a fully parametric proportional hazards mode…

stat.ME2019

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…

stat.ME2019

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…

stat.ME2018

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…

stat.ME2018

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…

stat.ME2016

Pseudo minimum phi-divergence estimator for multinomial logistic regression with complex sample design

Elena Castilla, Nirian Martin, Leandro Pardo

This article develops the theoretical framework needed to study the multinomial logistic regression model for complex sample design with pseudo minimum phi-divergence estimators. T…