Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Bayesian marked spatial point processes model for basketball shot
  chart   The success rate of a basketball shot may be higher at locations where a
player makes more shots. For a marked spatial point process, this means that
the mark and the intensity are associated. We propose a Bayesian joint model
for the mark and the intensity of marked point processes, where the intensity
is incorporated in the mark model as a covariate. Inferences are done with a
Markov chain Monte Carlo algorithm. Two Bayesian model comparison criteria, the
Deviance Information Criterion and the Logarithm of the Pseudo-Marginal
Likelihood, were used to assess the model. The performances of the proposed
methods were examined in extensive simulation studies. The proposed methods
were applied to the shot charts of four players (Curry, Harden, Durant, and
James) in the 2017--2018 regular season of the National Basketball Association
to analyze their shot intensity in the field and the field goal percentage in
detail. Application to the top 50 most frequent shooters in the season suggests
that the field goal percentage and the shot intensity are positively associated
for a majority of the players. The fitted parameters were used as inputs in a
secondary analysis to cluster the players into different groups.

9
The categories of this paper are: nlin
28
The categories of this paper are: alg-geom
8
The categories of this paper are: hep-ex
6
The categories of this paper are: astro-ph
25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
1
The categories of this paper are: cs
35
The categories of this paper are: mtrl-th
27
The categories of this paper are: comp-gas
24
The categories of this paper are: dg-ga
26
The categories of this paper are: bayes-an
36
The categories of this paper are: cmp-lg