58 citations · 131 across the 9 of their papers we have counts for
9 papers
Some Clustering-based Change-point Detection Methods Applicable to High Dimension, Low Sample Size Data
Trisha Dawn, Angshuman Roy, Alokesh Manna +1
Detection of change-points in a sequence of high-dimensional observations is a very challenging problem, and this becomes even more challenging when the sample size (i.e., the sequ…
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…
On Generalizations of Some Distance Based Classifiers for HDLSS Data
Sarbojit Roy, Soham Sarkar, Subhajit Dutta +1
In high dimension, low sample size (HDLSS) settings, classifiers based on Euclidean distances like the nearest neighbor classifier and the average distance classifier perform quite…
On high-dimensional modifications of some graph-based two-sample tests
Soham Sarkar, Rahul Biswas, Anil K. Ghosh
Testing for the equality of two high-dimensional distributions is a challenging problem, and this becomes even more challenging when the sample size is small. Over the last few dec…
On perfect clustering of high dimension, low sample size data
Soham Sarkar, Anil K. Ghosh
Popular clustering algorithms based on usual distance functions (e.g., Euclidean distance) often suffer in high dimension, low sample size (HDLSS) situations, where concentration o…
On Affine Invariant Depth Classifiers based on an Adaptive Choice of
Subhajit Dutta, Anil K. Ghosh
In this article, we use L depth for classification of multivariate data, where the value of is chosen adaptively using observations from the training sample. While many dep…