The VG AM package for negative binomial regression

Yee Thomas W.

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The VG AM package for negative binomial regression

机译：VG AM包装用于负二项式回归

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Negative binomial (NB) regression is the most common full-likelihood method for analysing count data exhibiting overdispersion with respect to the Poisson distribution. Usually most practitioners are content to fit one of two NB variants, however other important variants exist. It is demonstrated here that the VGAMR package can fit them all under a common statistical framework founded upon a generalised linear and additive model approach. Additionally, other modifications such as zero-altered (hurdle), zero-truncated and zero-inflated NB distributions are naturally handled. Rootograms are also available for graphically checking the goodness of fit. Two data sets and some recently added features of the VGAM package are used here for illustration.

机译：负二项式（NB）回归是用于分析表现出过度分布的计数数据的最常见的全似然方法。通常，大多数从业者都是满足于两个NB变体中的一种，但存在其他重要的变体。这里证明了VGAMR包可以根据在广义线性和添加剂模型方法上创立的常见统计框架下所有的VGAMR包装。另外，自然地处理诸如零变化（障碍物），零截断和零充气的NB分布的其他修改。 Rootomars也可用于图形检查合适的良好。此处使用两个数据集和VGAM包的一些最近添加的功能用于说明。

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来源
《Australian & New Zealand journal of statistics》 |2020年第1期|116-131|共16页
作者
Yee Thomas W.;
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Univ Auckland Dept Stat Private Bag 92019 Auckland 1142 New Zealand;

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正文语种 eng
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关键词
overdispersion; R; rootogram; vector generalised additive models; vector generalised linear models; zero alteration; zero inflation; zero truncation;

机译：过分分解;R;rootogrog;矢量广义添加剂模型;矢量广义线性模型;零改变;零充气;零截断;

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The VG AM package for negative binomial regression

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