TY - JOUR
T1 - On Improving the Posterior Predictive Distribution of the Difference Between two Independent Poisson Distribution
AU - Sadeghkhani, Abdolnasser
PY - 2022/11/1
Y1 - 2022/11/1
N2 - This paper addresses the exact Bayesian analysis of the difference between two independent Poisson distributions with means μ1 and μ2 respectively, known as the Skellam distribution with parameters (μ1, μ2). We develop a closed form for the posterior predictive distribution of the future distribution under the order constraint of μ1 > μ2. This kind of constraint is quite common and useful in applications specially in sports data analysis. We show that the proposed distribution estimator outperforms other types of distribution estimators in the literature. We use a simulation study with an example regarding the prediction in soccer games to show the performance of the proposed method.
AB - This paper addresses the exact Bayesian analysis of the difference between two independent Poisson distributions with means μ1 and μ2 respectively, known as the Skellam distribution with parameters (μ1, μ2). We develop a closed form for the posterior predictive distribution of the future distribution under the order constraint of μ1 > μ2. This kind of constraint is quite common and useful in applications specially in sports data analysis. We show that the proposed distribution estimator outperforms other types of distribution estimators in the literature. We use a simulation study with an example regarding the prediction in soccer games to show the performance of the proposed method.
KW - 62E15
KW - Kullback–Leibler divergence function
KW - order constraint
KW - Plug–in type distribution estimator
KW - Posterior predictive distribution
KW - Primary: 62C10; Secondary: 62F30
KW - Skellam distribution
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85131538691&origin=inward
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=85131538691&origin=inward
U2 - 10.1007/s13571-022-00284-3
DO - 10.1007/s13571-022-00284-3
M3 - Article
SN - 0976-8386
VL - 84
SP - 765
EP - 777
JO - Sankhya B
JF - Sankhya B
IS - 2
ER -