Efficient estimation for semiparametric varying- coefficient partially linear regression models with current status data

This article considers a semiparametric varying-coefficient partially linear regression model with current status data. The semiparametric varying-coefficient partially linear regression model which is a generalization of the partially linear regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A Sieve maximum likelihood estimation method is proposed and the asymptotic properties of the proposed estimators are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. The convergence rate of the estimator for the unknown smooth function is obtained and the estimator for the unknown parameter is shown to be asymptotically efficient and normally distributed. Simulation studies are conducted to examine the small-sample properties of the proposed estimates and a real dataset is used to illustrate our approach.     

Efficient estimation of a varying-coefficient partially linear binary regression model

This article considers a semiparametric varying-coefficient partially linear binary regression model. The semiparametric varying-coefficient partially linear regression binary model which is a generalization of binary regression model and varying-coefficient regression model that allows one to explore the possibly nonlinear effect of a certain covariate on the response variable. A Sieve maximum likelihood estimation method is proposed and the asymptotic properties of the proposed estimators are discussed. One of our main objects is to estimate nonparametric component and the unknowen parameters simultaneously. It is easier to compute, and the required computation burden is much less than that of the existing two-stage estimation method. Under some mild conditions, the estimators are shown to be strongly consistent. The convergence rate of the estimator for the unknown smooth function is obtained, and the estimator for the unknown parameter is shown to be asymptotically efficient and normally distributed. Simulation studies are carried out to investigate the performance of the proposed method.     

随机删失单函数型指标模型条件众数估计的渐近正态性

基于单函数型指标模型,构造了该模型下条件密度和条件众数的估计量,研究了 α-混合函数型数据在响应变量随机删失的情况下的条件密度和条件众数估计量的渐近正态分布,用模拟研究说明单函数型指标模型条件众数估计的有效性.     

关于半参数函数关系模型的渐近正态性

本文研究固定设计的半参数函数关系模型.利用权函数和广义最小二乘法得出未知参数和未知函数的估计,在一定的条件下证明了估计是强相合的,并且渐近地服从正态分布.     

关于半参数函数关系模型的渐近正态性

本文研究固定设计的半参数函数关系模型.利用权函数和广义最小二乘法得出未知参数和未知函数的估计,在一定的条件下证明了估计是强相合的,并且渐近地服从正态分布.     

Nested case-control analysis with general additive-multiplicative hazard models

This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo...     

指数分布定时截尾寿命试验失效率的近似置信区间

本文研究了指数分布大样本定时截尾寿命试验，给出了总试验时间的极限分布；并给出了失效率的近似置信区间。