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