Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A fully Bayesian strategy for high-dimensional hierarchical modeling
  using massively parallel computing   Markov chain Monte Carlo (MCMC) is the predominant tool used in Bayesian
parameter estimation for hierarchical models. When the model expands due to an
increasing number of hierarchical levels, number of groups at a particular
level, or number of observations in each group, a fully Bayesian analysis via
MCMC can easily become computationally demanding, even intractable. We
illustrate how the steps in an MCMC for hierarchical models are predominantly
one of two types: conditionally independent draws or low-dimensional draws
based on summary statistics of parameters at higher levels of the hierarchy.
Parallel computing can increase efficiency by performing embarrassingly
parallel computations for conditionally independent draws and calculating the
summary statistics using parallel reductions. During the MCMC algorithm, we
record running means and means of squared parameter values to allow convergence
diagnosis and posterior inference while avoiding the costly memory transfer
bottleneck. We demonstrate the effectiveness of the algorithm on a model
motivated by next generation sequencing data, and we release our implementation
in R packages fbseq and fbseqCUDA.

31
The categories of this paper are: ao-sci
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
21
The categories of this paper are: adap-org
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
0
The categories of this paper are: hep-ph
6
The categories of this paper are: astro-ph