Arnab Maity

TL;DR: Simulation studies show that the Bayesian method and parameter cascading method are comparable, and both outperform other available methods in terms of estimation accuracy.

TL;DR: This paper proposes a variable selection technique, based on adopting a generalized functional linear model framework and using a penalized likelihood method that simultaneously controls the sparsity of the model and the smoothness of the corresponding coefficient functions by adequate penalization.

TL;DR: A multivariate regression based on kernel machine is constructed to facilitate the joint evaluation of multimarker effects on multiple phenotypes and illustrates the utility of the multivariate kernel machine method through the Clinical Antipsychotic Trails of Intervention Effectiveness antibody study.

TL;DR: This work proposes a general framework of functional mixed effects model for within-unit and within-subunit variations are modeled through two separate sets of principal components; the subunit level functions are allowed to be correlated.

TL;DR: Practical strategies for KM testing when multiple candidate kernels are present based on constructing composite kernels and based on efficient perturbation procedures are proposed and demonstrated to lead to substantially improved power over poor choices of kernels and only modest differences in power vs. using the best candidate kernel.