Predictive Model Assessment for Count Data
Predictive Model Assessment for Count Data
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DOI：
10.1111/j.1541-0420.2009.01191.x
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发表时间：
2009-12-01
期刊：
影响因子：
1.9
通讯作者：
Held, Leonhard
中科院分区：
文献类型：
--
作者：
Czado, Claudia;Gneiting, Tilmann;Held, Leonhard
我们讨论了概率预报的评估工具和计数数据统计模型的批判。我们的建议包括一个非随机版本的概率积分变换，边际校准图，和适当的评分规则，如预测偏差。在案例研究中，我们批评专利数据的计数回归模型，并评估贝叶斯年龄-时期-队列模型在德国喉癌计数的预测性能。该工具箱适用于贝叶斯或经典和参数或非参数设置以及任何类型的有序离散结果。
P>We discuss tools for the evaluation of probabilistic forecasts and the critique of statistical models for count data. Our proposals include a nonrandomized version of the probability integral transform, marginal calibration diagrams, and proper scoring rules, such as the predictive deviance. In case studies, we critique count regression models for patent data, and assess the predictive performance of Bayesian age-period-cohort models for larynx cancer counts in Germany. The toolbox applies in Bayesian or classical and parametric or nonparametric settings and to any type of ordered discrete outcomes.