Bayesian variable selection with shrinking and diffusing priors
NN Narisetty, X He - 2014 - projecteuclid.org
Bayesian variable selection with shrinking and diffusing priors Page 1 The Annals of Statistics
2014, Vol. 42, No. 2, 789–817 DOI: 10.1214/14-AOS1207 © Institute of Mathematical Statistics …
2014, Vol. 42, No. 2, 789–817 DOI: 10.1214/14-AOS1207 © Institute of Mathematical Statistics …
Multilocus genetic analysis of brain images
The quest to identify genes that influence disease is now being extended to find genes that
affect biological markers of disease, or endophenotypes. Brain images, in particular, provide …
affect biological markers of disease, or endophenotypes. Brain images, in particular, provide …
[HTML][HTML] Scalable Bayesian variable selection using nonlocal prior densities in ultrahigh-dimensional settings
Bayesian model selection procedures based on nonlocal alternative prior densities are
extended to ultrahigh dimensional settings and compared to other variable selection …
extended to ultrahigh dimensional settings and compared to other variable selection …
Consistent high-dimensional Bayesian variable selection via penalized credible regions
HD Bondell, BJ Reich - Journal of the American Statistical …, 2012 - Taylor & Francis
For high-dimensional data, particularly when the number of predictors greatly exceeds the
sample size, selection of relevant predictors for regression is a challenging problem …
sample size, selection of relevant predictors for regression is a challenging problem …
Bayesian model selection for high-dimensional data
NN Narisetty - Handbook of statistics, 2020 - Elsevier
High-dimensional data, where the number of features or covariates can even be larger than
the number of independent samples, are ubiquitous and are encountered on a regular basis …
the number of independent samples, are ubiquitous and are encountered on a regular basis …
Genetic architecture of root and shoot ionomes in rice (Oryza sativa L.)
JN Cobb, C Chen, Y Shi, LG Maron, D Liu… - Theoretical and Applied …, 2021 - Springer
Key message Association analysis for ionomic concentrations of 20 elements identified
independent genetic factors underlying the root and shoot ionomes of rice, providing a …
independent genetic factors underlying the root and shoot ionomes of rice, providing a …
Case-control genome-wide association study of rheumatoid arthritis from Genetic Analysis Workshop 16 using penalized orthogonal-components regression-linear …
Currently, genome-wide association studies (GWAS) are conducted by collecting a massive
number of SNPs (ie, large p) for a relatively small number of individuals (ie, small n) and …
number of SNPs (ie, large p) for a relatively small number of individuals (ie, small n) and …
A supervised weeding method to cluster high dimensional predictors with application to job market analysis
Y Li, J Bi, J Liu, Y Yang - Journal of Applied Statistics, 2024 - Taylor & Francis
The clustering of high-dimensional predictors draws increasing attention in various scientific
areas, such as text mining and biological data analysis. In standard clustering procedures …
areas, such as text mining and biological data analysis. In standard clustering procedures …
Large‐scale identification of expression quantitative trait loci in Arabidopsis reveals novel candidate regulators of immune responses and other processes
The extensive phenotypic diversity within natural populations of Arabidopsis is associated
with differences in gene expression. Transcript levels can be considered as inheritable …
with differences in gene expression. Transcript levels can be considered as inheritable …
Simultaneous genome-wide association studies of anti-cyclic citrullinated peptide in rheumatoid arthritis using penalized orthogonal-components regression
Genome-wide associations between single-nucleotide polymorphisms and clinical traits
were simultaneously conducted using penalized orthogonal-components regression. This …
were simultaneously conducted using penalized orthogonal-components regression. This …