In this paper, Poisson time series models are considered to describe the number of field goals made by a basketball team or player at both the game (within-season) and the minute (within-game) level. To deal with the existence of temporal autocorrelation in the data, the model is endowed with a doubly self-exciting structure, following the INGARCH(1,1) specification. To estimate the model at the within-game level, a divide-and-conquer procedure, under a Bayesian framework, is carried out. The model is tested with a selection of NBA teams and players from the 2018-2019 season.
翻译：双重自激兴奋Poisson模型用于描述NBA篮球得分水平
翻译后的摘要：
本文考虑使用Poisson时间序列模型来描述一个篮球团队或球员在比赛（赛季内）和分钟（比赛内）级别上投篮命中次数。为了处理数据中存在的时间自相关性，模型被赋予了双重自激兴奋结构，遵循INGARCH（1，1）规范。为了在比赛内部水平上估计模型，我们在贝叶斯框架下执行了一种分而治之的过程。该模型经过从2018-2019赛季选出的一些NBA球队和球员的测试。
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