no code implementations • 9 Nov 2021 • Fan Dai, Karin S. Dorman, Somak Dutta, Ranjan Maitra
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 that needs to be understood.
no code implementations • 13 Jun 2020 • Dongjin Li, Somak Dutta, Vivekananda Roy
We develop a Bayesian variable selection method, called SVEN, based on a hierarchical Gaussian linear model with priors placed on the regression coefficients as well as on the model space.
Methodology Computation
no code implementations • 27 Jul 2019 • 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 observations than number of variables.
