68 citations · 377 across the 50 of their papers we have counts for
57 papers
A Composite Divergence Approach to Robust Multivariate Estimation under Cellwise and Casewise Contamination
Abhik Ghosh, Claudio Agostinelli, Ayanendranath Basu
Composite likelihood (CL) methods provide a computationally efficient alternative to full likelihood inference for complex multivariate models by replacing the joint likelihood wit…
Universally Optimal Robustness-Efficiency Tradeoffs for a General Class of Minimum Divergence Estimators
Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1
Balancing the efficiency of an estimator under ideal conditions against its robustness under contamination remains a central challenge in robust statistics. While minimum divergenc…
Semiparametric Robust Estimation of Population Location
Ananyabrata Barua, Ayanendranath Basu
Real-world measurements often comprise a dominant signal contaminated by a noisy background. Robustly estimating the dominant signal in practice has been a fundamental statistical…
Robust Rank Estimation for Noisy Matrices
Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu
Estimating the true rank of a noisy data matrix is a fundamental problem underlying techniques such as principal component analysis, matrix completion, etc. Existing rank estimatio…
Asymptotic breakdown point analysis of the minimum density power divergence estimator under independent non-homogeneous setups
Suryasis Jana, Subhrajyoty Roy, Ayanendranath Basu +1
The minimum density power divergence estimator (MDPDE) has gained significant attention in the literature of robust inference due to its strong robustness properties and high asymp…
Characterization of Generalized Alpha-Beta Divergence and Associated Entropy Measures
Subhrajyoty Roy, Supratik Basu, Abhik Ghosh +1
Minimum divergence estimators provide a natural framework for robust (parametric) statistical inference. Useful properties of several such divergence measures, including, the Helli…