Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Estimation in Dirichlet random effects models   We develop a new Gibbs sampler for a linear mixed model with a Dirichlet
process random effect term, which is easily extended to a generalized linear
mixed model with a probit link function. Our Gibbs sampler exploits the
properties of the multinomial and Dirichlet distributions, and is shown to be
an improvement, in terms of operator norm and efficiency, over other commonly
used MCMC algorithms. We also investigate methods for the estimation of the
precision parameter of the Dirichlet process, finding that maximum likelihood
may not be desirable, but a posterior mode is a reasonable approach. Examples
are given to show how these models perform on real data. Our results complement
both the theoretical basis of the Dirichlet process nonparametric prior and the
computational work that has been done to date.

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The categories of this paper are: q-bio
25
The categories of this paper are: patt-sol
26
The categories of this paper are: bayes-an
34
The categories of this paper are: chem-ph
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
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The categories of this paper are: q-fin
12
The categories of this paper are: nucl-th
4
The categories of this paper are: cond-mat
14
The categories of this paper are: math-ph
1
The categories of this paper are: cs
19
The categories of this paper are: eess
36
The categories of this paper are: cmp-lg