1) random erasure
随机删除
2) random censorship
随机删失
1.
Asymptotic properties of estimators in semiparametric regression model under random censorship;
随机删失下半参数回归模型中估计的渐近性质
2.
In this paper the convergence rates of the improved kernel regression estimate and the kernel regression estimate are obtained under random censorship.
本文在随机删失场合下，得到了回归函数ｍ（ｘ）＝Ｅ［Ｙ／ｘ］的改良核估计及核估计的收敛速度，该结果与完全数据场合完全一致。
3.
This article discusses the parameter estimation problem in the two-parameter exponential distribution based on complete sample, type I censoring sample and random censorship sample, respectively.
本文讨论了双参数指数分布的参数估计问题,在完全数据试验、定数截尾试验和随机删失试验下分别基于线性回归方法(由文献[7]提出)、Bayes方法和极大似然方法给出了双参数指数分布位置参数和刻度参数的估计。
3) non-random censoring data
非随机删失
1.
Based on the iteration algorithm which is proposed to deal with non-random censoring data in past paper,the data-filling method is modified so that the virtual complete data obtained from the algorithm is much closer to the real complete data in the case of Weibull distribution under type I censoring data.
基于作者曾提出的处理非随机删失数据的迭代算法,针对Weibull分布相同定时截尾型试验数据,通过改变数据的填补方式,在保证由算法所得的参数估计的相合性和不变性的前提下,使得改进后的算法所得的虚拟完全数据更接近于真实的完全数据。
2.
Based on the moment invariance criterion and corresponding algorithm which is proposed to deal with non-random censoring data, in this paper, the consistency of estimator is proved in the case of the Weibull distribution under type I censoring data, through controlling the quartile probability of the data filling algorithm.
利用处理非随机删失数据的矩不变准则及相应算法,本文针对Weibuu分布相同定时截尾型试验数据,通过控制算法中填充数据的分位概率,证明了通过迭代算法所得到的参数估计的相合性。
4) random right censorship
随机右删失
1.
The large sample property of kernel smoothing product limit estimation under random right censorship;
随机右删失下核光滑乘积限估计的大样本性质
5) delete
[英][dɪ'li:t] [美][dɪ'lit]
删去，删除
6) delete
[英][dɪ'li:t] [美][dɪ'lit]
删除;删去
补充资料：随机数和伪随机数
随机数和伪随机数
random and pseudo-randan numbers
随机数和伪随机数【喇间佣1 al川牌”山一喇闭..m.山娜;cJI了，a如曰e”nce，口oc月卿成.以叹“c月a】 数亡。(特别，二进制数:。)，其顺序出现，满足某种统计正则性(见概率论(probability Uleory)).人们是这样区别随机数(mndomn切mbe比)和伪随机数(PSeudo一mn由mn切mbe岛)的，前者由随机的装置来生成，而后者是用算术算法构造的.总是假设(出于较好或较差的理由)所得(或所构造)的序列具有频率性质，这些性质对于具有分布函数F(z)的某随机变量心独立实现的一个序列来说是“典型的”;因此人们称作根据规律F(习分布的(独立的)随机数.最经常使用的例子为:在区间【O，l]上均匀分布的随机数亡。，尸(亡。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条