• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>AStA Advances in statistical analysis >On Poisson-exponential-Tweedie models for ultra-overdispersed count data
【24h】

On Poisson-exponential-Tweedie models for ultra-overdispersed count data

机译：关于泊松指数-Tweedie模型，用于超过度分散的计数数据

获取原文
获取原文并翻译 | 示例
       
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

We introduce a new class of Poisson-exponential-Tweedie (PET) mixture in the framework of generalized linear models for ultra-overdispersed count data. The mean-variance relationship is of the form m + m(2) + phi m(p), where phi and pare the dispersion and Tweedie power parameters, respectively. The proposed model is equivalent to the exponential-Poisson-Tweedie models arising from geometric sums of Poisson-Tweedie random variables. In this respect, the PET models encompass the geometric versions of Hermite, Neyman Type A, Polya-Aeppli, negative binomial and Poisson-inverse Gaussian models. The algorithms we shall propose allow to estimate the real power parameter, which works as an automatic distribution selection. Instead of the classical Poisson, zero-shifted geometric is presented as the reference count distribution. Practical properties are incorporated into the PET of new relative indexes of dispersion and zero-inflation phenomena. Simulation studies demonstrate that the proposed model highlights unbiased and consistent estimators for large samples. Illustrative practical applications are analysed on count data sets, in particular, PET models for data without covariates and PET regression models. The PET models are compared to Poisson-Tweedie models showing that parameters of both models are adopted to data.
机译：我们在推广线性模型框架中介绍了一类新的泊松指数-weedie（PET）混合物，用于超过度分散的计数数据。平均方差关系是M + M（2）+ PHI M（P）的形式，其中PHI分别分别削减分散和TWEEDIE功率参数。所提出的模型相当于从泊松 - 跳序随机变量的几何和的指数-Poisson-Tweedie模型。在这方面，宠物模型包括Hermite，奈曼类型A，Polya-Aeppli，负二项式和泊松逆高斯模型的几何形式。我们将建议允许估计实际功率参数，该参数适用于自动分配选择。而不是经典的泊松，零移位的几何是参考计数分布。实际属性纳入了分散和零充气现象的新相对指标的PET。仿真研究表明，所提出的模型突出了大型样品的无偏见和一致的估计。在计数数据集上分析了说明性实际应用，特别是宠物模型，用于无协调因子和宠物回归模型。将PET模型与Poisson-Tweedie模型进行比较，显示两种模型的参数被采用数据。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号