68 citations · 377 across the 50 of their papers we have counts for
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Robust and Efficient Parameter Estimation based on Censored Data with Stochastic Covariates
Abhik Ghosh, Ayanendranath Basu
Analysis of random censored life-time data along with some related stochastic covariables is of great importance in many applied sciences like medical research, population studies…
The Minimum S-Divergence Estimator under Continuous Models: The Basu-Lindsay Approach
Abhik Ghosh, Ayanendranath Basu
Robust inference based on the minimization of statistical divergences has proved to be a useful alternative to the classical maximum likelihood based techniques. Recently Ghosh et…
The Logarithmic Super Divergence and its use in Statistical Inference
Avijit Maji, Abhik Ghosh, Ayanendranath Basu
This paper introduces a new superfamily of divergences that is similar in spirit to the S-divergence family introduced by Ghosh et al. (2013). This new family serves as an umbrella…
The Logarithmic Super Divergence and Statistical Inference : Asymptotic Properties
Avijit Maji, Abhik Ghosh, Ayanendranath Basu
Statistical inference based on divergence measures have a long history. Recently, Maji, Ghosh and Basu (2014) have introduced a general family of divergences called the logarithmic…
On the Robustness of a Divergence based Test of Simple Statistical Hypotheses
Abhik Ghosh, Ayanendranath Basu, Leandro Pardo
The most popular hypothesis testing procedure, the likelihood ratio test, is known to be highly non-robust in many real situations. Basu et al. (2013a) provided an alternative robu…
Robust Estimation in Generalised Linear Models : The Density Power Divergence Approach
Abhik Ghosh, Ayanendranath Basu
The generalised linear model (GLM) is a very important tool for analysing real data in biology, sociology, agriculture, engineering and many other application domain where the rela…