探究了在响应变量随机缺失情形下部分线性变系数模型的模型选择和模型平均问题.基于借补方法和Profile最小二乘技术,建立了局部误设定框架下该模型的FIC准则(focused information criterion)和FMA(frequentist model average)估计量,并...探究了在响应变量随机缺失情形下部分线性变系数模型的模型选择和模型平均问题.基于借补方法和Profile最小二乘技术,建立了局部误设定框架下该模型的FIC准则(focused information criterion)和FMA(frequentist model average)估计量,并探究了FIC和FMA的理论性质.模拟研究表明了所提出方法的优越性.最后将提出的方法应用于CD4数据.展开更多
In this study,the authors proposed upper tolerance limits for the gamma mixture distribution based on generalized fiducial inference,and an MCMC simulation is performed to sample from the generalized fiducial distribu...In this study,the authors proposed upper tolerance limits for the gamma mixture distribution based on generalized fiducial inference,and an MCMC simulation is performed to sample from the generalized fiducial distributions.The simulation results and a real hydrological data example show that the proposed tolerance limits are more efficient.展开更多
文摘探究了在响应变量随机缺失情形下部分线性变系数模型的模型选择和模型平均问题.基于借补方法和Profile最小二乘技术,建立了局部误设定框架下该模型的FIC准则(focused information criterion)和FMA(frequentist model average)估计量,并探究了FIC和FMA的理论性质.模拟研究表明了所提出方法的优越性.最后将提出的方法应用于CD4数据.
文摘In this study,the authors proposed upper tolerance limits for the gamma mixture distribution based on generalized fiducial inference,and an MCMC simulation is performed to sample from the generalized fiducial distributions.The simulation results and a real hydrological data example show that the proposed tolerance limits are more efficient.