Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Model choice in separate families: A comparison between the FBST and the
  Cox test   Tests of separate families of hypotheses were initially considered by Cox
(1961,1962) In this work, the Fully Bayesian Significance Test, FBST, is
evaluated for discriminating between the lognormal, gamma and Weibull models
whose families of distributions are separate. Considering a linear mixture
model including all candidate distributions, the FBST tests the hypotheses on
the mixture weights in order to calculate the evidence measure in favor of each
one. Additionally, the density functions of the mixture components are
reparametrized in terms of the common parameters, the mean and the variance of
the population, since the comparison between the models is based on the same
dataset, i.e, on the same population. Reparametrizing the models in terms of
the common parameters also allows one to reduce the number of the parameters to
be estimated. In order to evaluate the performance of the procedure, some
numerical results based on simulated sample points are given. In these
simulations, the results of FBST are compared with those of the Cox test. Two
applications examples illustrating the procedure for uncensored dataset are
also presented.
  Keywords: Model choice; Separate Models; Mixture model; Significance test;
FBST; Cox Test

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The categories of this paper are: astro-ph
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