1 citations · 1 across the 8 of their papers we have counts for
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Structured Screen-and-Select for Ultra-High-Dimensional Variable Selection
Nilotpal Sanyal, Padmore N. Prempeh
Ultra-high-dimensional data, with p far exceeding n, are common in genomics and biomedical research. Marginal screening can miss active predictors with weak marginal signals, espec…
Robust and Sparse Group Dynamic Causal Modeling via Student-t Parametric Empirical Bayes and Nonlocal Priors
Godfred Arhin, Nilotpal Sanyal
Dynamic causal modeling (DCM) estimates directed effective connectivity, while parametric empirical Bayes (PEB) supports group inference using subject-specific posterior summaries.…
Competing-Risk Cure Models: A Comprehensive Systematic Review of Methodological Literature
Nilotpal Sanyal
Competing-risk cure models describe time-to-event populations with individuals immune to all event types or an event of interest, yet literature is fragmented across model families…
Resolution-Adaptive Compact-Support Priors for Bayesian Wavelet Denoising
Nilotpal Sanyal
We propose a resolution-adaptive Bayesian wavelet denoising method for noisy one-dimensional signals. Its central innovation is a spike-and-slab prior whose continuous slab mixes a…
Comparative Review of Modern Competing Risk Methods in High-dimensional Settings
Paul M. Djangang, Summer S. Han, Nilotpal Sanyal
Competing risk analysis accounts for multiple mutually exclusive events, improving risk estimation over traditional survival analysis. Despite methodological advancements, a compre…
Nonlocal Prior Mixture-Based Bayesian Wavelet Regression with Application to Noisy Imaging and Audio Data
Nilotpal Sanyal
We propose a novel Bayesian wavelet regression approach using a three-component spike-and-slab prior for wavelet coefficients, combining a point mass at zero, a moment (MOM) prior,…
High-dimensional iterative variable selection for accelerated failure time models
Nilotpal Sanyal
We propose an iterative variable selection method for the accelerated failure time model using high-dimensional survival data. Our method pioneers the use of the recently proposed…
Iterative variable selection for high-dimensional data with binary outcomes
Nilotpal Sanyal
We propose an iterative variable selection scheme for high-dimensional data with binary outcomes. The scheme adopts a structured screen-and-select framework and uses non-local prio…