Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Individual adaptation: an adaptive MCMC scheme for variable selection
  problems   The increasing size of data sets has lead to variable selection in regression
becoming increasingly important. Bayesian approaches are attractive since they
allow uncertainty about the choice of variables to be formally included in the
analysis. The application of fully Bayesian variable selection methods to large
data sets is computationally challenging. We describe an adaptive Markov chain
Monte Carlo approach called Individual Adaptation which adjusts a general
proposal to the data. We show that the algorithm is ergodic and discuss its use
within parallel tempering and sequential Monte Carlo approaches. We illustrate
the use of the method on two data sets including a gene expression analysis
with 22 577 variables.

14
The categories of this paper are: math-ph
7
The categories of this paper are: hep-th
1
The categories of this paper are: cs
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
13
The categories of this paper are: quant-ph
35
The categories of this paper are: mtrl-th