基于贝叶斯框架的双变量泊松模型的体育数据分析

Sabina Shahin
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引用次数: 0

摘要

双变量分布模型通常用于分析体育数据和各个领域的数据。这些模型用于分析具有两个因变量的离散计数数据。在本文中,我们使用了二元泊松和对角膨胀的二元泊松回归模型。我们在贝叶斯框架中提出了一种与数据扩充相结合的估计过程。对于参数估计,我们对两个模型都使用高斯先验和贝塔先验。为了说明我们建议的模型的拟合性能,我们对英超联赛的数据进行了实际数据分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sports Data Analysis by using Bivariate Poisson Models in the Bayesian Framework
Bivariate distribution models are commonly used to analyze sports data and data from various fields. These models are used to analyze discrete count data with two dependent variables in the data. In this research article, we have used Bivariate Poisson and Diagonally Inflated Bivariate Poisson regression models. We have proposed an estimation procedure in the Bayesian framework in conjunction with the augmentation of data. For parameter estimation, we use Gaussian priors and beta priors for both models. To illustrate the fitting performances of our suggested models we have performed real data analysis on English Premier League soccer data.
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