| 1. | Estimation for a class of semiparametric regression model with censored data
截尾数据下一类半参数回归模型的估计 |
| 2. | The weighted kernel estimators of nonparametricregression function with censored data
截尾数据非参数回归函数加权核估计 |
| 3. | Weighted kernel estimator of nonparametric regression functions with censored data of sequences
相依截尾数据非参数回归函数加权核估计 |
| 4. | Bayesian estimation for the parameter of exponential distribution under multiply type - censoring
定数截尾数据缺失场合下双参数指数分布参数的贝叶斯估计 |
| 5. | Chen jiading , wei zhongpeng , wang tao , wang qingcheng , the lower confidence limit for reliability parameters based on the interval censored data , icm 2002
陈家鼎，魏中鹏，王涛等，一类截尾数据下贮存可靠度评估方法研究，中国国防科学技术报告， 2003 . 9 |
| 6. | Hamada and wu ( 1991 ) identified important location effects by imputing the censored data . and bihua has considered identification of both location and dispersion effects from unreplicated factorial experiment with right - censored data
对于这样的截尾数据， hamada与wu ( 1991 )通过对截尾数据补值，给出了模型选择以及鉴别和估计位置效应的方法。 |
| 7. | ( 1 ) after giving the various methods for getting the point estimations of parameters based on the type - censored data . we do the comparison of the accuracy of all these point estimations . in the portion , the pivotal quantity used to get the approximate interval estimation of parameters is also derived
( 1 )给出求定数截尾数据埸合下参数的点估计的多种方法，比较了各种点估计的精度；构造了求参数近似区间估计的枢轴量，并通过模拟说明本文方法是可行的。 |
| 8. | The method of identifying and estimating the factor location effect is the main content of reseatch in the traditional experiment design with complete data ( the observation of experiment is known exactly ) . in the standard method the identification of dispersion effects typically requires replications with the fixed factor levels
在完全数据(即试验的观测值无截尾数据)情形下，因子位置效应的鉴别和估计方法是传统试验设计的主要研究内容；而对于因子的散度效应鉴别，传统方法需要在固定因子水平组合下作若干次重复试验。 |
| 9. | Firstly , we estimate the variance and the mean of each cell with maximum likelihood ; secondly , we identify the important dispersion effects based on least squares analysis of the logarithm of within - replication variance ; last , we identify the important location effects based on weighted least squares analysis of the mean of each cell . a simulation study also demonstrates its superiority over some existing methods . an experiment for the robust design of thermostat is used to illustrate the method
本文对带有右截尾数据的有重复因子试验，提出了另一种分析位置效应和散度效应的方法：首先，在每一个试验点，对重复试验观察值用极大似然法估计出均值和方差；其次，用每个试验点方差估计值的对数作为响应变量与各因子建立回归模型，鉴别出显著的散度效应；之后，采用加权最小二乘法鉴别出比较显著的位置效应。 |
