参数估计

Furthermore, computer simulation aimed at Weibull distribution and lognormal distribution is processed, and results show that the provided method is feasible and easy to implement.

论文还对Weibull分布和对数正态分布作了相应的计算机模拟，结果表明所给参数估计方法是容易施行并且行之有效的。

In this paper, EM algorithm is used to estimate the parameters of exponential distribution, Weibull distribution and lognormal distribution based on randomly right censored data.

本文将EM算法用于随机右删失数据下指数分布、Weibull分布和对数正态分布的参数估计中。

For each method, detailed procedure of calculating the confidence lower bound of the availability is given.

迄今为止，文献中应用WCF方法所处理的是参数估计量相互独立的情形。

The Cramer-Rao lower bound theory is a very important part of the theory of signal detection and is of great value to parameters estimation.

Cramer-Rao下界是信号检测理论中的重要部分，它对参数估计有相当大的价值。

Furthermore, we can deal with the dependence of multivariate assets and marginal distribution of univariate asset respectively as are to the testing of parameters estimation.

并且可将多资产相依结构和单个资产边际分布分开来处理利，对二者进行分别进行参数估计检验。

About Generalized Kantorovich Inequality ,selecting proper norm of matrix formulation and its upper limit applies to estimating parameter of relative efficiency of linear model.

对于广义 Kantorovich不等式，选用适当的矩阵度量并给出相应的界，可以应用在线性模型的参数估计的相对效率问题上。

Given the assumption of analysis-of-variance model, the text selection can be transformed to a linear parameter estimation problem, which can then be solved by a greedy matroid cover algorithm.

在方差分析模型的假设下，最优文本选择就转化为线性参数估计问题，相当于寻找拟阵的最小代价覆盖集，从而可通过贪心算法求解。

Furthermore, by the aid of maximin principle, we construct a model-robust optimal design for the consideration of parameter estimation.

更进一步地，我们利用小中取大原则建构一个对个别模型成立下有关参数估计问题均具稳健性质的实验设计。

On the basis of the information of experimental study, models of comonomer conversion, and the molecular weight distribution under the condition of the maximum mixednees in a continuous stirred tank reactor were established.

在实验研究的基础上，建立了连续搅拌釜式反应器中丁二烯／苯乙烯阴离子溶液共聚合数学模型并进行了模型的参数估计和模拟计算。

The maximum likelihood method for parameter estimation has an extensive application in the intelligence information processing.

本文从凸泛函的对偶表示的角度，深入探讨了具有隐变量的模型极大似然参数估计的变分学习方法。

But we don't care about Battlegrounds.

但我们并不在乎沙场中的显露。

Ah! don't mention it, the butcher's shop is a horror.

啊！不用提了。提到肉，真是糟透了。