Arun Krishna

Works (2)

Updated: August 6th, 2023 12:15

2010 journal article

Joint Variable Selection for Fixed and Random Effects in Linear Mixed-Effects Models

BIOMETRICS, 66(4), 1069–1077.

By: H. Bondell n, A. Krishna n & S. Ghosh n 

Contributors: H. Bondell n, A. Krishna n & S. Ghosh n 

author keywords: Adaptive LASSO; Constrained EM algorithm; Linear mixed model; Modified Cholesky decomposition; Penalized likelihood; Variable selection
MeSH headings : Algorithms; Biometry / methods; Computer Simulation; Humans; Likelihood Functions; Linear Models; Models, Statistical
TL;DR: This method is based on a penalized joint log likelihood with an adaptive penalty for the selection and estimation of both the fixed and random effects and enjoys the Oracle property, in that, asymptotically it performs as well as if the true model was known beforehand. (via Semantic Scholar)
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018

2008 journal article

Bayesian variable selection using an adaptive powered correlation prior

JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 139(8), 2665–2674.

By: A. Krishna n, H. Bondell n & S. Ghosh n 

Contributors: A. Krishna n, H. Bondell n & S. Ghosh n 

author keywords: Bayesian variable selection; Collinearity; Powered correlation prior; Zellner's g-prior
TL;DR: An extension of the Zellner's prior is proposed in this article which allow for a power parameter on the empirical covariance of the predictors which helps control the degree to which correlated predictors are smoothed towards or away from one another. (via Semantic Scholar)
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Sources: Web Of Science, ORCID, NC State University Libraries
Added: August 6, 2018

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