参数估计

In particular, for recurrent event data, we proposed a novel nonparametric estimator of the survival function and obtained an efficient estimator of the expected total number of events for counting processes. Also we established asymptotic properties of these estimators and investigated nonparametric estimation of survival functions, density functions and hazard functions under various types of incomplete data.

在重复事件发生的情况下，创新地提出了一种生存函数的非参数估计，获得了计数过程中预期事件总数的估计以及这些估计的大样本性质，并在其他各种不完全数据下对生存函数，概率密度和失效率函数等非参数估计进行了深刻研究。

From the results of expanded state estimation application, which is a representative parameter estimation method proposed before, it often happened that the parameters could not be estimated or estimated imprecisely.

扩展状态估计法是一种有代表性的参数估计方法，在该算法的实际应用中，发现支路参数不可估计或者估计结果不合理的现象时有发生。

On the base, using the knowledge about matrix operations, we study the admissibility of parameter estimators in multilinear model and growth curve model.

在此基础上，利用矩阵运算的知识，进一步研究了多元线性模型和增长曲线模型中参数估计的可容许性，获得了参数估计在指定的估计类和全体估计类中可容许的充要条件或充分条件。

Standard nonparametric tests and confidence intervals for continuous and categorical data; nonparametric estimation of quantiles; robust estimation of location and scale parameters.

非参数和稳健方法：连续和类别数据的标准非参数检验和置信区间，分位数的非参数估计，阶和位置参数的稳健估计，传统方法的效果比较。

Because of the sampling processing, we can take the simple concave domain analysis and ICM optimization in two different levels, so as to make both the parameter estimation and optimization much easier to implement, while delivering a satisfactory result; The third one is based on the multi-resolution analysis, robust statistics and majority game theory. 4. Propose a new clustering algorithm based on the entropy concept, which is used for unsupervised segmentation of color images.

重点讨论非监督的图象分割问题，并给出了三种新方法：一是基于贝叶斯学习和全局竞争策略的方法，把参数估计和图象分割有机地结合在一起；二是基于分层的框架，从抽样定理出发，在两个不同的层次上使用简单的凹域分析和ICM优化，可以使得参数估计和优化问题都变得简单易行，并得到满意的结果；三是基于多级分析、鲁棒统计的参数估计和多数博弈论的优化算法。

Based on the stacking of data matrix, real-processing of signal subspace, complex shift invariance equation and joint eigenvalue estimation, an algorithm is presented to solve this problem and handle the estimation jointly.

基于数据矩阵的重新排列、信号子空间的实数化处理、复数移不变方程以及联合特征值估计，推导出联合估计参数的ESPRIT类算法，该算法将参数估计问题转化为3个具有实特征值的实数矩阵的联合特征值估计问题。

This paper researches the improvement of the vector of unknown parameter α and the vector of random-effect parameter β, including GLSE and LSE in some conditions, discusses the relevant properties of parameter's estimation, and explains the thought of using its unbiased estimator replaced when the variance is unknown.

本文研究了未知参数向量a和随机系数β的参数估计的改进，包括在一定条件下的GLSE和LSE，并讨论了参数估计的有关性质及说明了在方差未知时，用其无偏估计代替的思想。

And then Mashal and Beyone method is used to estimate parameters of t-Copula.

通过参数估计方法比较运用Mashal and Beyone提出的参数估计方法对其进行参数估计。

To reduce the computational burden under the parametric model of mixed-spectrum, the proposed method decouples the estimation for parameters of sinusoids and of AR clutter.

该方法利用混合谱参数化模型，通过对正弦参数估计及AR杂波参数估计的解耦处理，降低了谱估计过程的计算复杂度。

The widely used method are trial solution and the least square method. They need huge calculations and their results are less reliable. A new kind of intelligent genetic algorithm was employed to get the optimal parameter. Using it in the（ model has proved its reliability for production forecast of oilfield.

各种油气田产量预报模型的应用关键在于参数估计，常规参数估计方法为试凑法和最小二乘法，工作量大，可靠性差，所以引入了一种新型遗传算法求取参数最优估计值，并通过遗传算法在Γ模型中的应用实例说明了该方法在油气产量预报中的可行性。

The split between the two groups can hardly be papered over.

这两个团体间的分歧难以掩饰。

This approach not only encourages a greater number of responses, but minimizes the likelihood of stale groupthink.

这种做法不仅鼓励了更多的反应，而且减少跟风的可能性。