Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: MCMC algorithms for Bayesian variable selection in the logistic
  regression model for large-scale genomic applications   In large-scale genomic applications vast numbers of molecular features are
scanned in order to find a small number of candidates which are linked to a
particular disease or phenotype. This is a variable selection problem in the
"large p, small n" paradigm where many more variables than samples are
available. Additionally, a complex dependence structure is often observed among
the markers/genes due to their joint involvement in biological processes and
pathways. Bayesian variable selection methods that introduce sparseness through
additional priors on the model size are well suited to the problem. However,
the model space is very large and standard Markov chain Monte Carlo (MCMC)
algorithms such as a Gibbs sampler sweeping over all p variables in each
iteration are often computationally infeasible. We propose to employ the
dependence structure in the data to decide which variables should always be
updated together and which are nearly conditionally independent and hence do
not need to be considered together. Here, we focus on binary classification
applications. We follow the implementation of the Bayesian probit regression
model by Albert and Chib (1993) and the Bayesian logistic regression model by
Holmes and Held (2006) which both lead to marginal Gaussian distributions. We
in- vestigate several MCMC samplers using the dependence structure in different
ways. The mixing and convergence performances of the resulting Markov chains
are evaluated and compared to standard samplers in two simulation studies and
in an application to a real gene expression data set.

8
The categories of this paper are: hep-ex
19
The categories of this paper are: eess
11
The categories of this paper are: hep-lat
1
The categories of this paper are: cs
29
The categories of this paper are: funct-an
36
The categories of this paper are: cmp-lg
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
7
The categories of this paper are: hep-th