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本文研究了不等式约束条件下部分线性回归模型的参数估计问题,利用最优化方法和贝叶斯方法,给出了不等式约束条件下部分线性回归模型的最小二乘核估计和最佳贝叶斯估计,并且证明了在一定条件下,带约束条件的最小二乘核估计在均方误差意义下要优于无约束条件的最小二乘核估计。 相似文献
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独立约束条件下线性模型的参数估计 总被引:2,自引:0,他引:2
司存瑞 《纯粹数学与应用数学》2000,16(3):87-89
对线性回归的未知参数估计问题,在某些种假设的条件下已有结论,对有约束条件的情况下,线性回归模型中参数估计如何,本文给出了带有独立的约束条件下线性回归模型中参数β的最小二乘估计。 相似文献
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本文讨论条件矩限制回归模型的参数估计.使用非参数估计方法给出条件密度和条件均值的估计,在此基础上给出参数的广义矩估计.进一步讨论了估计的渐近正态性. 相似文献
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奇异线性模型基于变换观测值的最佳线性无偏估计 总被引:4,自引:0,他引:4
对于奇异线性回归模型Y丫:X9十c,c”(o,∑),其中∑主o,X的秩任意,本文一般地考察观测值的线性变换铲:9r对于系数d的最佳线性无偏估计(BLUE)的影响,得到了由变换带来的参数估计变化的一般结果,文献[1]关于线性变换保持BLUE最优性的主要结果成为该结果的一个推论,本文还证明了这种变换模型的参数估计问题等价于一个广义均值漂移模型的参数估计问题。 相似文献
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讨论有不服从发生时,临床试验数据EV模型中的参数估计和检验问题.在以前结果的基础上,文中给出模型中公共参数的一个改进估计,提出了一个药物治疗效果的检验方法.最后通过模拟研究考察上述估计和检验的效果。 相似文献
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在不确定性线性模型中,参数通常带有不确定的先验信息,它们影响着参数估计及其精度.本文利用椭球集合对含有先验信息的参数进行描述,建立基于椭球不确定性的线性模型,并提出相应的估计算法.本文主要采用直接迭代算法解决参数估计中的权值分配问题,给出参数估计可容许性的充要条件.最后,通过实证分析算法的有效性,解决权值分配对平差解的影响. 相似文献
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在一般的线性回归模型中,自变量都被认为是没有误差的准确值。然而当所有观测变量都可能存在误差时,通常的统计方法就会产生偏差。本文利用数据分组的思想,提出分组最小二乘估计法进行参数估计,减少了参数估计的偏差。并且在只知道误差界的情况下,利用分组最小二乘能给出几种度量误差模型的相合估计。 相似文献
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Arnaud Doucet Vladislav B. Tadić 《Annals of the Institute of Statistical Mathematics》2003,55(2):409-422
Particle filtering techniques are a set of powerful and versatile simulation-based methods to perform optimal state estimation
in nonlinear non-Gaussian state-space models. If the model includes fixed parameters, a standard technique to perform parameter
estimation consists of extending the state with the parameter to transform the problem into an optimal filtering problem.
However, this approach requires the use of special particle filtering techniques which suffer from several drawbacks. We consider
here an alternative approach combining particle filtering and gradient algorithms to perform batch and recursive maximum likelihood
parameter estimation. An original particle method is presented to implement these approaches and their efficiency is assessed
through simulation. 相似文献
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本文利用变点统计学和黄金分割法讨论有多个变点的离散回归方程的交点估计和参数估计,文中提出基于黄金分割法搜索最佳变点估计和同时得到参数估计的最小二乘算法,还讨论该算法在控制领域的应用,数值模拟结果显示本文算法能给出良好的变点及参数的估计值。 相似文献
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B. L. S. Prakasa Rao 《随机分析与应用》2017,35(3):533-541
We consider the problem of optimal estimation of the vector parameter θ of the drift term in a sub-fractional Brownian motion. We obtain the maximum likelihood estimator as well as Bayesian estimator when the prior distribution is Gaussian. 相似文献
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本文在绝对损失下构造了双边截断型分布族参数的经验Bayes估计,并在合适的条件下证明了该估计的渐近最优性.最后,给出两个有关本文主要结果的例子. 相似文献
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产品可靠度的E-Bayes估计 总被引:2,自引:1,他引:1
提出了参数估计的一种新方法——E-Bayes估计法.对Pascal分布,给出了可靠度的E-Bayes估计的定义(在先验分布中有一个超参数情形),在此基础上给出了可靠度的E-Bayes估计,并给出了可靠度的E-Bayes估计性质——E-Bayes估计和多层Bayes估计的关系.最后,给出了模拟算例,结果表明本文提出的E-Bayes估计法可行且便于工程应用. 相似文献
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二项分布参数多层Bayes和E Bayes估计的性质 总被引:1,自引:0,他引:1
讨论无失效数据下二项分布参数E Bayes估计和多层Bayes估计的性质,证明二项参数的多层Bayes估计和E Bayes估计渐近相等,且E Bayes估计值小于多层Bayes估计值. 相似文献
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指数分布参数多层Bayes和E Bayes估计的性质 总被引:1,自引:0,他引:1
本文讨论无失效数据下指数分布参数多层Bayes估计和E Bayes估计的性质,在超参数分别取两种不同的先验分布下,证明参数的多层Bayes估计和E Bayes估计渐近相等,且多层Bayes估计值小于E Bayes估计值. 相似文献
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Arnoud C.M. van Rooij Frits H. Ruymgaart 《Annals of the Institute of Statistical Mathematics》2001,53(4):781-798
Recovery of the unknown parameter in an abstract inverse estimation model can be based on regularizing the inverse of the operator defining the model. Such regularized-inverse type estimators are constructed with the help of a version of the spectral theorem due to Halmos, after suitable preconditioning. A lower bound to the minimax risk is obtained exploiting the van Trees inequality. The proposed estimators are shown to be asymptotically optimal in the sense that their risk converges to zero, as the sample size tends to infinity, at the same rate as this lower bound. The general theory is applied to deconvolution on locally compact Abelian groups, including both indirect density and indirect regression function estimation. 相似文献
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当参数的先验分布为伽玛分布时,在复合Linex对称损失函数下得到了Kumaraswamy分布参数θ的唯一的Bayes估计,多层Bayes估计和E-Bayes估计,并通过数值模拟说明了所给参数估计的稳健性和精确性. 相似文献
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Shankar C. Subramanian Swaroop Darbha K.R. Rajagopal 《Nonlinear Analysis: Hybrid Systems》2008,2(4):1113-1124
It may happen that the equations governing the response of dynamical systems have some parameters whose values may not be known a priori and have to be obtained using parameter estimation schemes. In this article, we present a parameter estimation scheme for a class of sequential hybrid systems. By hybrid systems, we refer to those systems whose response is described by different governing equations corresponding to various regimes/modes of operation along with some criteria to switch between the same. In a sequential hybrid system, the different modes are arranged in a specific sequence and the system can switch from a given mode to either the previous mode or the following mode in this sequence. Here, we consider those systems whose governing equations consist of ordinary differential equations and algebraic equations. The conditions for switching between the various modes (referred to as transition conditions) are in the form of linear inequalities involving the system output. We shall first consider the case where the transition conditions are known completely. We present a parameter update scheme along with sufficient conditions that will guarantee bounded parameter estimation errors. Then, we shall consider the case where the transition conditions are not known in the sense that some parameters in these conditions are not known. We present a parameter estimation scheme for this case. We illustrate the performance of the parameter estimation scheme in both cases with some examples. 相似文献