activity
20222026
most citedFunctional varying-coefficient model under heteroskedasticity with application to DTI data

1 citations · 1 across the 8 of their papers we have counts for

collaborators

9 papers

math.ST2026

Nonparametric Regression with Measurement Error in Banach Spaces

Pratim Guha Niyogi, Priyadarshi Dey

We consider nonparametric regression with a Banach-space-valued predictor where the covariate takes values in a general separable Banach space. Our primary objective is to develop…

stat.AP2026

Covariate-Adjusted Functional Principal Components Analysis for Modeling Hazard Rates of Physical Activity in the US Population

Md Rokibul Hasan, Pratim Guha Niyogi

Physical activity plays a vital role in human health. Its entire distribution differs among people. Commonly used summary measures cannot describe this distributional pattern. We p…

stat.ME2026

Scalar-on-distribution regression via generalized odds with applications to accelerometry-assessed disability in multiple sclerosis

Pratim Guha Niyogi, Muraleetharan Sanjayan, Kathryn C. Fitzgerald +2

Distributional representations of data collected using digital health technologies have been shown to outperform scalar summaries for clinical prediction, with carefully quantified…

stat.AP2024

Hazard and Beyond: Exploring Five Distributional Representations of Accelerometry Data for Disability Discrimination in Multiple Sclerosis

Pratim Guha Niyogi, Muraleetharan Sanjayan, Dmitri Volfson +3

Research on modeling the distributional aspects in sensor-based digital health (sDHT) data has grown significantly in recent years. Most existing approaches focus on using individu…

stat.ME2024

Identifying arbitrary transformation between the slopes in scalar-on-function regression

Pratim Guha Niyogi, Subhra Sankar Dhar

In this article, we study whether the slope functions of two scalar-on-function regression models in two samples are associated with any arbitrary transformation along the vertical…

stat.ME2024

Quadratic inference with dense functional responses

Pratim Guha Niyogi, Ping-Shou Zhong

We address the challenge of estimation in the context of constant linear effect models with dense functional responses. In this framework, the conditional expectation of the respon…

stat.ME2023

A tensor based varying-coefficient model for multi-modal neuroimaging data analysis

Pratim Guha Niyogi, Martin A. Lindquist, Tapabrata Maiti

All neuroimaging modalities have their own strengths and limitations. A current trend is toward interdisciplinary approaches that use multiple imaging methods to overcome limitatio…

stat.ME2023

Inspecting discrepancy between multivariate distributions using half-space depth based information criteria

Pratim Guha Niyogi, Subhra Sankar Dhar

This article inspects whether a multivariate distribution is different from a specified distribution or not, and it also tests the equality of two multivariate distributions. In th…

stat.ME2022★ 1 cited

Functional varying-coefficient model under heteroskedasticity with application to DTI data

Pratim Guha Niyogi, Ping-Shou Zhong, Xiaohong Joe Zhou

In this paper, we develop a multi-step estimation procedure to simultaneously estimate the varying-coefficient functions using a local-linear generalized method of moments (GMM) ba…