首先利用非对称的LINEX损失函数对双指数分布族刻度参数进行了经验贝叶斯估计，并讨论了该估计的性质，给出了收敛速度。
First, we obtain the empirical Bayesian estimator of the scale parameter for the double exponential distribution based on LINEX loss function and the convergence rate of the estimate.
研究了随机右截尾情形下两个指数分布的参数估计。
This paper studies the parameters' estimation of two exponential distributions under randomly right censoring.
正态混合模型还可以用来对那些不能用标准的参数分布族来拟和的总体进行密度估计或近似。
The normal mixed distribution model can be used to get probability density or to simulate population which can not be fitted by standard parameters distribution classes.
采用零截尾计数模型分析，不仅可以解决零截尾计数分布问题，且参数估计结果更准确，拟合效果更合理。
Zero-truncated count model could not only solve the issue of zero-truncated count distribution, but also the parameter estimates were more accurate, the fitting results were more reasonable.
因此在JM模型的基础上，提出了排错时间为负指数分布的软件可靠性模型及本模型的极大似然参数估计方法。
Based on JM model, we propose a software reliability prediction model involving fault-remove time which followed exponential distribution.
利用极大似然估计以及方向极大似然估计的概念，分别得到了双参数指数分布的参数的估计量，并证明了双参数指数分布中的两个参数满足双曲线型关。
In this paper, we used the concepts of the maximum likehood estimate and the direction maximum likehood estimate to give two kinds of estimates for two-parameter exponential distribution.
对指数分布下的双截尾数据和分段数据，给出了其参数矩估计的一种新的方法。
A new method of moment parameter estimation parameter is given by double side censored data and interval data in the exponential distribution.
最近，对指数分布的参数和正态分布的位置参数讨论了基于残缺观测数据的区间估计”，‘’。
Making use of two order statistics to construct a sample fonction for confidence interval estimation of the scale parameter, the probability density function of the sample function is discussed.
因此在JM模型的基础上，提出了排错时间为负指数分布的软件可靠性模型及本模型的极大似然参数估计方法。
A software reliability model for substation automation system based on improved JM model is set up in this paper.
因此在JM模型的基础上，提出了排错时间为负指数分布的软件可靠性模型及本模型的极大似然参数估计方法。
A software reliability model for substation automation system based on improved JM model is set up in this paper.
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