摘要
讨论响应变量带有不可忽略缺失数据的非线性均值方差模型的Bayes估计问题.缺失数据机制由logistic回归模型来指定,运用Gibbs抽样及MH算法得到模型参数和缺失数据机制参数的联合Bayes估计,模拟研究和实例分析展示上述模型和方法的可行性.
A Bayesian approach is proposed to analyze nonlinear mean and variance models,in which the responses are missing with non-ignorable missingness mechanism.The missingness mechanism is specified by a logistic model,Gibbs sampler and Metropolis-Hastings algorithm is employed to obtain the joint Bayesian estimates of model parameters and missingness mechanism parameters.The proposed methodology is demonstrated by several simulation studies and a real example.
作者
赵远英
唐安民
段星德
庞一成
ZHAO Yuan-ying;TANG An-min;DU AN Xing-de;PANG Yi-cheng(College of Mathematics and Information Science,Guiyang University,Guiyang 550005,China;Department of Statistics,Yunnan University,Kunming 650091,China;School of Mathematics and Statistics,Guizhou University of Finance and Economics,Guiyang 550025,China)
出处
《数学的实践与认识》
北大核心
2019年第21期157-165,共9页
Mathematics in Practice and Theory
基金
国家自然科学基金(11761016,11501073,11561074,11661015)
贵阳市科技局贵阳学院科技专项基金(GYU-KYZ(2019-2020)PT04-04)
