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Article overview
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High dimensional Single Index Bayesian Modeling of the Brain Atrophy over time | | Arkaprava Roy
; Subhashis Ghosal
; Kingshuk Roy Choudhury
; | | Date: |
Tue, 19 Dec 2017 01:33:34 GMT (1831kb,D) | | Abstract: | We study the effects of gender, APOE genes, age, genetic variation and
Alzheimer’s disease on the atrophy of the brain regions. In the real data
analysis section, we add a subject specific random effect to capture subject
inhomogeneity. A nonparametric single index Bayesian model is proposed to study
the data with B-spline series prior on the unknown functions and Dirichlet
process scale mixture of zero mean normal prior on the distributions of the
random effects. Posterior consistency of the proposed model without the random
effect is established for a fixed number of regions and time points with
increasing sample size. A new Bayesian estimation procedure for high
dimensional single index model is introduced in this paper. Performance of the
proposed Bayesian method is compared with the corresponding least square
estimator in the linear model with LASSO and SCAD penalization on the high
dimensional covariates. The proposed Bayesian method is applied on a dataset of
748 individuals with 620,901 SNPs and 6 other covariates for each individual. | | Source: | arXiv, 1712.6743 | | Services: | Forum | Review | PDF | Favorites | |
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