1 citations · 1 across the 6 of their papers we have counts for
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Robust K-means Clustering using the Density Power Divergence Measure
Anirban Mondal, Paromita Banerjee, Abhijit Mandal
We introduce a robust clustering method, MK-means DPD, that estimates cluster centers and covariance matrices using density power divergence (DPD) measures combined with Mahalanobi…
Robust Density Power Divergence Estimates for Panel Data Models
Abhijit Mandal, Beste Hamiye Beyaztas, Soutir Bandyopadhyay
The panel data regression models have become one of the most widely applied statistical approaches in different fields of research, including social, behavioral, environmental scie…
A robust specification test in linear panel data models
Beste Hamiye Beyaztas, Soutir Bandyopadhyay, Abhijit Mandal
The presence of outlying observations may adversely affect statistical testing procedures that result in unstable test statistics and unreliable inferences depending on the distort…
Robust Inference Using the Exponential-Polynomial Divergence
Pushpinder Singh, Abhijit Mandal, Ayanendranath Basu
Density-based minimum divergence procedures represent popular techniques in parametric statistical inference. They combine strong robustness properties with high (sometimes full) a…
Robust Variable Selection Criteria for the Penalized Regression
Abhijit Mandal, Samiran Ghosh
We propose a robust variable selection procedure using a divergence based M-estimator combined with a penalty function. It produces robust estimates of the regression parameters an…
An Optimal Test for the Additive Model with Discrete or Categorical Predictors
Abhijit Mandal
In multivariate nonparametric regression the additive models are very useful when a suitable parametric model is difficult to find. The backfitting algorithm is a powerful tool to…