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含不可忽略缺失数据非线性再生散度模型参数的Bayes估计
  • ISSN号：1001-9626
  • 期刊名称：生物数学学报
  • 时间：0
  • 页码：357-364
  • 分类：O212.1[理学—概率论与数理统计;理学—数学]
  • 作者机构：[1]楚雄师范学院计算机科学与技术系,云南楚雄675000, [2]楚雄师范学院地理科学与旅游管理系,云南楚雄675000, [3]云南大学应用统计研究中心,云南昆明650091
  • 相关基金：国家自然科学基金资助项目（10961026）;云南省教育厅科研基金资助项目（06Y046F）;院级科研骨干专项资助项目（05YJGGl2）
  • 相关项目：复杂数据非线性模型的统计推断及其应用
作者： 和燕|彭燕梅|唐年胜|
关键词： 不可忽略缺失数据机制, 非线性再生散度模型, Dirichlet先验分布, BAYES方法, MCMC, 协变量, Nonignorable missing mechanism , Nonlinear reproductive dispersion mod-els , Dirichlet prior distribution , Markov chain Monte-Carlo method , covariate variables
中文摘要：

给出协变量带有不可忽略缺失数据的非线性再生散度模型的Bayes方法，缺失数据机制由Logistic回归模型来确定．Gibbs抽样技术和Metropolis—Hastings算法（简称MH算法）用来得到模型参数、缺失数据机制中回归系数的联合Bayes估计，并用实例加以说明．

英文摘要：

Bayesian method is developed to analyze nonlinear reproductive dispersion mod-els in which the covariate variables may be missing with nonignorable missingness mechanism. The missingness is specified by a logistic regression model.the Gibbs sampler and the MH algorithm is used to obtain the joint Bayesian estimates of parameters.A real example are used to illustrate the methodology.

同期刊论文项目
复杂数据非线性模型的统计推断及其应用
期刊论文 27
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期刊信息
  • 《生物数学学报》
  • 北大核心期刊（2008版）
  • 主管单位:中国数学会
  • 主办单位:中国数学会生物数学学会
  • 主编：陈兰荪
  • 地址：辽宁省鞍山师范学院158号
  • 邮编：114007
  • 邮箱：smbjbm@tom.com
  • 电话：0412-2960893
  • 国际标准刊号：ISSN：1001-9626
  • 国内统一刊号：ISSN：34-1071/O1
  • 邮发代号:
  • 获奖情况:
  • 国内外数据库收录:
  • 美国数学评论（网络版）,德国数学文摘,日本日本科学技术振兴机构数据库,中国北大核心期刊（2004版）,中国北大核心期刊（2008版）
  • 被引量:5686