activity
20112026
most citedA Re-defined and Generalized Percent-Overlap-of-Activation Measure for Studies of fMRI Reproducibility and its Use in Identifying Outlier Activation Maps

63 citations · 148 across the 10 of their papers we have counts for

collaborators
Showing stat.MEShow all

10 papers · 1 filter

stat.ME2026

Boxplots and quartile plots for grouped and periodic angular data

Joshua D. Berlinski, Fan Dai, Ranjan Maitra

Angular observations, or observations lying on the unit circle, arise in many disciplines and require special care in their description, analysis, interpretation and visualization.…

stat.ME2022

Elliptically-Contoured Tensor-variate Distributions with Application to Improved Image Learning

Carlos Llosa-Vite, Ranjan Maitra

Statistical analysis of tensor-valued data has largely used the tensor-variate normal (TVN) distribution that may be inadequate when data comes from distributions with heavier or l…

stat.ME20211 cited

Exploratory Factor Analysis of Data on a Sphere

Fan Dai, Karin S. Dorman, Somak Dutta +1

Data on high-dimensional spheres arise frequently in many disciplines either naturally or as a consequence of preliminary processing and can have intricate dependence structure tha…

stat.ME2021

Fast model-based clustering of partial records

Emily M. Goren, Ranjan Maitra

Partially recorded data are frequently encountered in many applications and usually clustered by first removing incomplete cases or features with missing values, or by imputing mis…

stat.ME2019

A Matrix--free Likelihood Method for Exploratory Factor Analysis of High-dimensional Gaussian Data

Fan Dai, Somak Dutta, Ranjan Maitra

This paper proposes a novel profile likelihood method for estimating the covariance parameters in exploratory factor analysis of high-dimensional Gaussian datasets with fewer obser…

stat.ME2019

Classification with the matrix-variate- distribution

Geoffrey Z. Thompson, Ranjan Maitra, William Q. Meeker +1

Matrix-variate distributions can intuitively model the dependence structure of matrix-valued observations that arise in applications with multivariate time series, spatio-temporal…