Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Approximate Bayesian Computation with composite score functions   Both Approximate Bayesian Computation (ABC) and composite likelihood methods
are useful for Bayesian and frequentist inference, respectively, when the
likelihood function is intractable. We propose to use composite likelihood
score functions as summary statistics in ABC in order to obtain accurate
approximations to the posterior distribution. This is motivated by the use of
the score function of the full likelihood, and extended to general unbiased
estimating functions in complex models. Moreover, we show that if the composite
score is suitably standardised, the resulting ABC procedure is invariant to
reparameterisations and automatically adjusts the curvature of the composite
likelihood, and of the corresponding posterior distribution. The method is
illustrated through examples with simulated data, and an application to
modelling of spatial extreme rainfall data is discussed.

17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
26
The categories of this paper are: bayes-an
11
The categories of this paper are: hep-lat
23
The categories of this paper are: solv-int
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn
29
The categories of this paper are: funct-an
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg