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本文对NA样本,在一定条件下,研究了非参数回归函数导数核估计逐点强相合及一致强相合的收敛速度. 相似文献
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本文考虑在右侧随机截尾模型下,非参数回归函数核估计的强收敛问题,在一组自然的条件下,得到了与完全样本情况相当的收敛速度。 相似文献
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回归函数核估计的收敛速度 总被引:2,自引:0,他引:2
本文在P≥1的条件下,给出了回归函数m(x)的核估计m_n(x)的若干种p阶平均收敛速度,改进并推广了文献[1]及[2]中的若干结果。 相似文献
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本文研究了基于相依函数型数据非参数回归函数的核估计.利用稳健的方法,在一定条件下获得了与i.i.d.场合下类似的估计量的几乎完全收敛速度,推广了现有文献中的相关结论. 相似文献
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关于回归函数核估计的叠对数律 总被引:1,自引:0,他引:1
张团峰 《纯粹数学与应用数学》1996,12(2):52-56
讨论了非参数回归函数的核估计,用核估计误差分解方法,较弱条件下,到了回归函数核估计的叠对数值。 相似文献
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本文分别在截尾分布函数已知和未知两种情况下,构造了基于截尾样本的非参数固定设计模型回归函数的加权核估计,并研究了它们的一些收敛性质. 相似文献
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本文在刻度平方误差损失函数下导出了刻度指数族分布中参数的Bayes估计.利用核估计的方法构造了参数的经验Bayes估计,在适当条件下得到了经验Bayes估计的收敛速度,推广了文献中的相关结果. 相似文献
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双指数分布位置参数的经验Bayes估计问题 总被引:2,自引:0,他引:2
本文在平方损失下导出了双指数分布位置参数的Bayes估计,利用非参数方法构造了位置参数的经验Bayes(EB)估计.在适当的条件下,获得了EB估计的收敛速度.最后,给出了一个例子说明适合定理条件的先验分布是存在的. 相似文献
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Pan Jiazhu 《数学年刊B辑(英文版)》1998,19(2):239-248
§1.IntroductionSupposethatFisadistributionfunctionsuchthat,foranyx>0,limt→∞1-F(tx)1-F(t)=x-1γ,γ>0.(1.1)WecalγthetailindexofF.... 相似文献
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Takemi Yanagimoto Kazuo Anraku 《Annals of the Institute of Statistical Mathematics》1989,41(2):269-278
The possibility that the conditional maximum likelihood estimator (CMLE) is superior to the unconditional maximum likelihood estimator (UMLE) is discussed in examples where the residual likelihood is obstructive. We observe relatively smaller risks of the CMLE for a finite sample size. The models in the study include the normal, inverse Gauss, gamma, two-parameter exponential, logit, negative binomial and two-parameter geometric ones. 相似文献
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M. J. Silvapulle 《偏微分方程通讯》2013,38(4):829-835
Page1 (1981) claimed that there is a serious design flaw in some of the recent simulation studies of ridge estimators, in particular those in Hoerl, Kennard and Baldwin (1976) and Lawless and Wang (1976). Farebrother (1983) argued that the major criticism in Page1 (1981) is unsubstantiated. In this paper we obtain a series expansion for the mean squared error of the ordinary ridge estimator, use it to prove that Pagel's claim is incorrect and reinforce Farebrother's comments. 相似文献
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Ingrid Van Keilegom Noël Veraverbeke 《Annals of the Institute of Statistical Mathematics》2001,53(4):730-745
Consider a regression model in which the responses are subject to random right censoring. In this model, Beran studied the nonparametric estimation of the conditional cumulative hazard function and the corresponding cumulative distribution function. The main idea is to use smoothing in the covariates. Here we study asymptotic properties of the corresponding hazard function estimator obtained by convolution smoothing of Beran's cumulative hazard estimator. We establish asymptotic expressions for the bias and the variance of the estimator, which together with an asymptotic representation lead to a weak convergence result. Also, the uniform strong consistency of the estimator is obtained. 相似文献
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Claudia Angelini Daniela De Canditiis Frdrique Leblanc 《Journal of multivariate analysis》2003,85(2):267-291
We show that a nonparametric estimator of a regression function, obtained as solution of a specific regularization problem is the best linear unbiased predictor in some nonparametric mixed effect model. Since this estimator is intractable from a numerical point of view, we propose a tight approximation of it easy and fast to implement. This second estimator achieves the usual optimal rate of convergence of the mean integrated squared error over a Sobolev class both for equispaced and nonequispaced design. Numerical experiments are presented both on simulated and ERP real data. 相似文献
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《Communications in Nonlinear Science & Numerical Simulation》2014,19(7):2479-2492
In this paper, the state estimation problem is investigated for stochastic genetic regulatory networks (GRNs) with random delays and Markovian jumping parameters. The delay considered is assumed to be satisfying a certain stochastic characteristic. Meantime, the delays of GRNs are described by a binary switching sequence satisfying a conditional probability distribution. The aim of this paper is to design a state estimator to estimate the true states of the considered GRNs through the available output measurements. By using Lyapunov functional and some stochastic analysis techniques, the stability criteria of the estimation error systems are obtained in the form of linear matrix inequalities under which the estimation error dynamics is globally asymptotically stable. Then, the explicit expression of the desired estimator is shown. Finally, a numerical example is presented to show the effectiveness of the proposed results. 相似文献
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I. Rahimov 《Statistics & probability letters》2011,81(8):907-914
In this paper, we consider the conditional least squares estimator (CLSE) of the offspring mean of a branching process with non-stationary immigration based on the observation of population sizes. In the supercritical case, assuming that the immigration variables follow known distributions, conditions guaranteeing the strong consistency of the proposed estimator will be derived. The asymptotic normality of the estimator will also be proved. The proofs are based on direct probabilistic arguments, unlike the previous papers, where functional limit theorems for the process were used. 相似文献
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Marianna Pensky Brani Vidakovic 《Annals of the Institute of Statistical Mathematics》2001,53(4):681-690
Wavelet-based regression analysis is widely used mostly for equally-spaced designs. For such designs wavelets are superior to other traditional orthonormal bases because of their versatility and ability to parsimoniously describe irregular functions. If the regression design is random, an automatic solution is not available. For such non equispaced designs we propose an estimator that is a projection onto a multiresolution subspace in an associated multiresolution analysis. For defining scaling empirical coefficients in the proposed wavelet series estimator our method utilizes a probabilistic model on the design of independent variables. The paper deals with theoretical aspects of the estimator, in particular MSE convergence rates. 相似文献
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本文在{Xr,t∈N)是一个严平稳过程的假设下,用核估计的方法对未来状态XN+T的条件密度进行估计.在假设{Xt,t∈N)是α-混合过程的情况下,讨论了过程有限维密度核估计的期望与方差,以及过程条件密度核估计的偏及均方误差.在一定条件下,证明了估计的弱收敛性. 相似文献