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19952026
most citedHybridSN: Exploring 3D-2D CNN Feature Hierarchy for Hyperspectral Image Classification

1.9k citations

Showing 2019 · math.STShow all

6 papers · 2 filters

math.ST2019

On Robust Pseudo-Bayes Estimation for the Independent Non-homogeneous Set-up

Tuhin Majumder, Ayanendranath Basu, Abhik Ghosh

The ordinary Bayes estimator based on the posterior density suffers from the potential problems of non-robustness under data contamination or outliers. In this paper, we consider t…

math.ST2019★ 1 cited

Modified Lomax Model: A heavy-tailed distribution for fitting large-scale real-world complex networks

Swarup Chattopadhyay, Tanujit Chakraborty, Kuntal Ghosh +1

Real-world networks are generally claimed to be scale-free, meaning that the degree distributions follow the classical power-law, at least asymptotically. Yet, closer observation s…

math.ST2019

Higher Order Refinements by Bootstrap in Lasso and other Penalized Regression Methods

Debraj Das, Arindam Chatterjee, S. N. Lahiri

Selection of important covariates and to drop the unimportant ones from a high-dimensional regression model is a long standing problem and hence have received lots of attention in…

math.ST2019★ 12 cited

Bound on FWER for correlated normal distribution

Nabaneet Das, Subir K. Bhandari

In this paper,our main focus is to obtain an asymptotic bound on the family wise error rate (FWER) for Bonferroni-type procedure in the simultaneous hypotheses testing problem when…

math.ST2019★ 3 cited

Some New Copula Based Distribution-free Tests of Independence among Several Random Variables

Angshuman Roy, Anil Ghosh, Alok Goswami +1

Over the last couple of decades, several copula based methods have been proposed in the literature to test for the independence among several random variables. But these existing t…

math.ST2019★ 16 cited

A Scale-invariant Generalization of the Rényi Entropy, Associated Divergences and their Optimizations under Tsallis' Nonextensive Framework

Abhik Ghosh, Ayanendranath Basu

Entropy and relative or cross entropy measures are two very fundamental concepts in information theory and are also widely used for statistical inference across disciplines. The re…