116 citations · 1.2k across the 79 of their papers we have counts for
84 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…
A Componentwise Estimation Procedure for Multivariate Location and Scatter: Robustness, Efficiency and Scalability
Soumya Chakraborty, Ayanendranath Basu, Abhik Ghosh
Covariance matrix estimation is an important problem in multivariate data analysis, both from theoretical as well as applied points of view. Many simple and popular covariance matr…
Robust inference for linear regression models with possibly skewed error distribution
Amarnath Nandy, Ayanendranath Basu, Abhik Ghosh
Traditional methods for linear regression generally assume that the underlying error distribution, equivalently the distribution of the responses, is normal. Yet, sometimes real li…
Robust Principal Component Analysis using Density Power Divergence
Subhrajyoty Roy, Ayanendranath Basu, Abhik Ghosh
Principal component analysis (PCA) is a widely employed statistical tool used primarily for dimensionality reduction. However, it is known to be adversely affected by the presence…
Towards -cm intensity mapping at with uGMRT using the tapered gridded estimator III: Foreground removal
Khandakar Md Asif Elahi, Somnath Bharadwaj, Srijita Pal +8
Neutral hydrogen (HI) -cm intensity mapping (IM) is a promising probe of the large-scale structures in the Universe. However, a few orders of magnitude brighter foregrounds obs…
Analysis of the rSVDdpd Algorithm: A Robust Singular Value Decomposition Method using Density Power Divergence
Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu
The traditional method of computing singular value decomposition (SVD) of a data matrix is based on a least squares principle, thus, is very sensitive to the presence of outliers.…
Asymptotic Breakdown Point Analysis for a General Class of Minimum Divergence Estimators
Subhrajyoty Roy, Abir Sarkar, Abhik Ghosh +1
Robust inference based on the minimization of statistical divergences has proved to be a useful alternative to classical techniques based on maximum likelihood and related methods.…
Towards -cm intensity mapping at with uGMRT using the tapered gridded estimator II: Cross-polarization power spectrum
Kh. Md. Asif Elahi, Somnath Bharadwaj, Abhik Ghosh +8
Neutral hydrogen () -cm intensity mapping (IM) offers an efficient technique for mapping the large-scale structures in the universe. We introduce the 'Cross' Tapered G…
Multi-scale analysis of rural and urban areas: A case study of Indian districts
Abhik Ghosh, Souvik Chattopadhay, Banasri Basu
This paper explores the extension of the idea of allometric urban scaling law to study the scaling behaviour of Indian districts, with both the urban and rural population. To proce…
Robust and Efficient Estimation in Ordinal Response Models using the Density Power Divergence
Arijit Pyne, Subhrajyoty Roy, Abhik Ghosh +1
In real life, we frequently come across data sets that involve some independent explanatory variable(s) generating a set of ordinal responses. These ordinal responses may correspon…
Exponential Consistency of M-estimators in Generalized Linear Mixed Models
Andrea M. Bratsberg, Magne Thoresen, Abhik Ghosh
Generalized linear mixed models are powerful tools for analyzing clustered data, where the unknown parameters are classically (and most commonly) estimated by the maximum likelihoo…
Existence and Consistency of the Maximum Pseudo \b{eta}-Likelihood Estimators for Multivariate Normal Mixture Models
Soumya Chakraborty, Ayanendranath Basu, Abhik Ghosh
Robust estimation under multivariate normal (MVN) mixture model is always a computational challenge. A recently proposed maximum pseudo \b{eta}-likelihood estimator aims to estimat…
Robust Estimation of Average Treatment Effects from Panel Data
Sayoni Roychowdhury, Indrila Ganguly, Abhik Ghosh
In order to evaluate the impact of a policy intervention on a group of units over time, it is important to correctly estimate the average treatment effect (ATE) measure. Due to lac…
rSVDdpd: A Robust Scalable Video Surveillance Background Modelling Algorithm
Subhrajyoty Roy, Ayanendranath Basu, Abhik Ghosh
A basic algorithmic task in automated video surveillance is to separate background and foreground objects. Camera tampering, noisy videos, low frame rate, etc., pose difficulties i…
Robust adaptive Lasso in high-dimensional logistic regression
Ayanendranath Basu, Abhik Ghosh, María Jaenada +1
Penalized logistic regression is extremely useful for binary classification with large number of covariates (higher than the sample size), having several real life applications, in…
Strata-based Quantification of Distributional Uncertainty in Socio-Economic Indicators: A Comparative Study of Indian States
Abhik Ghosh, Olivia Mallick, Souvik Chattopadhay +1
This paper reports a comprehensive study of distributional uncertainty in a few socio-economic indicators across the various states of India over the years 2001-2011. We show that…
RaJIVE: Robust Angle Based JIVE for Integrating Noisy Multi-Source Data
Erica Ponzi, Magne Thoresen, Abhik Ghosh
With increasing availability of high dimensional, multi-source data, the identification of joint and data specific patterns of variability has become a subject of interest in many…
Demonstrating the Tapered Gridded Estimator (TGE) for the Cosmological HI 21-cm Power Spectrum using GMRT observations
Srijita Pal, Somnath Bharadwaj, Abhik Ghosh +1
We apply the Tapered Gridded Estimator (TGE) for estimating the cosmological 21-cm power spectrum from GMRT observations which corresponds to the neutral hydroge…
Robust Estimation under Linear Mixed Models: The Minimum Density Power Divergence Approach
Giovanni Saraceno, Abhik Ghosh, Ayanendranath Basu +1
Many real-life data sets can be analyzed using Linear Mixed Models (LMMs). Since these are ordinarily based on normality assumptions, under small deviations from the model the infe…
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…
Robust Clustering with Normal Mixture Models: A Pseudo -Likelihood Approach
Soumya Chakraborty, Ayanendranath Basu, Abhik Ghosh
As in other estimation scenarios, likelihood based estimation in the normal mixture set-up is highly non-robust against model misspecification and presence of outliers (apart from…
On regularization methods based on Rényi's pseudodistances for sparse high-dimensional linear regression models
Elena Castilla, Abhik Ghosh, María Jaenada +1
Several regularization methods have been considered over the last decade for sparse high-dimensional linear regression models, but the most common ones use the least square (quadra…
Interpreting LOFAR 21-cm signal upper limits at z~9.1 in the context of high-z galaxy and reionisation observations
Bradley Greig, Andrei Mesinger, Léon V. E. Koopmans +11
Using the latest upper limits on the 21-cm power spectrum at from the Low Frequency Array (LOFAR), we explore regions of parameter space which are inconsistent with t…
Foreground modelling via Gaussian process regression: an application to HERA data
Abhik Ghosh, Florent Mertens, Gianni Bernardi +70
The key challenge in the observation of the redshifted 21-cm signal from cosmic reionization is its separation from the much brighter foreground emission. Such separation relies on…