• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>Statistics and computing >Exact Bayesian modeling for bivariate Poisson data and extensions
【24h】

Exact Bayesian modeling for bivariate Poisson data and extensions

机译：用于双变量Poisson数据和扩展的精确贝叶斯建模

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

Bivariate count data arise in several different disciplines (epidemiology, marketing, sports statistics just to name a few) and the bivariate Poisson distribution being a generalization of the Poisson distribution plays an important role in modelling such data. In the present paper we present a Bayesian estimation approach for the parameters of the bivariate Poisson model and provide the posterior distributions in closed forms. It is shown that the joint posterior distributions are finite mixtures of conditionally independent gamma distributions for which their full form can be easily deduced by a recursively updating scheme. Thus, the need of applying computationally demanding MCMC schemes for Bayesian inference in such models will be removed, since direct sampling from the posterior will become available, even in cases where the posterior distribution of functions of the parameters is not available in closed form. In addition, we define a class of prior distributions that possess an interesting conjugacy property which extends the typical notion of conjugacy, in the sense that both prior and posteriors belong to the same family of finite mixture models but with different number of components. Extension to certain other models including multivariate models or models with other marginal distributions are discussed.
机译：双变量计数数据出现在几个不同的学科（流行病学，市场营销，体育统计等），而双变量泊松分布是泊松分布的概括，在建模此类数据中起着重要作用。在本文中，我们针对双变量Poisson模型的参数提出了一种贝叶斯估计方法，并提供了封闭形式的后验分布。结果表明，联合后验分布是条件独立的伽马分布的有限混合，可以通过递归更新方案轻松推导出其完整形式。因此，将消除在此类模型中为贝叶斯推理应用计算要求高的MCMC方案的需要，因为即使在参数函数的后验分布不可用封闭形式的情况下，也可以从后验进行直接采样。另外，我们定义了一类具有有趣的共轭性质的先验分布，它扩展了典型的共轭概念，从这个意义上说，先验和后验均属于有限混合模型的同一族，但分量数不同。讨论了对某些其他模型的扩展，包括多元模型或具有其他边际分布的模型。

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