共查询到17条相似文献,搜索用时 62 毫秒
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利用局部影响的方法对一般形式下的协方差分析模型进行了讨论.把数据点或数据子集的扰动拓展到更广泛的扰动模式并进行了局部影响评价,导出了一般形式下的协方差分析模型在方差扰动下局部影响的曲率度量. 相似文献
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本文研究了多元线性同归模型岭估计的影响分析问题.利用最小二乘估计方法,获得了多元协方差阵扰动模型与原模型参数阵之间的岭估计的一些关系式,给出了度量影响大小的基于岭估计的广义Cook距离. 相似文献
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该文研究了协方差阵扰动和数据删除对最佳线性无偏估计(BLUE)的影响问题, 给出了在约束条件下一般线性模型与在约束条件下Gauss-Markov模型及在约束条件下数据删除模型中回归参数β的BLUE之间的关系式. 作者还定义了度量影响大小的广义Cook距离DV并给出了DV的两个计算公式. 相似文献
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该文研究混合线性模型效应参数的Bayes局部影响评价问题.导出了混合线性模型在各种扰动下效应参数的Bayes局部影响度量,并给出了平衡单向分类随机效应模型下的一些结果.最后通过实例分析,以证实该文方法的有效性. 相似文献
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本文应用以Kullback-Leibler散度为基础的Bayesian局部影响方法,对具有Rao简单结构的多元T-模型进行了局部影响分析.在确定了先验分布假设下,详细地研究了这个模型的Bayesian Hessian矩阵,作为应用,特别考虑了常见的加权协方差扰动形式. 相似文献
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本文讨论具有一般协方差结构的增长曲线模型中未知参数矩阵的Bayes影响分析问题.在无信息先验分布假设下,K-L距离被用来评估指定响应阵对参数矩阵的后验分布的影响程度. 相似文献
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刘金山 《高校应用数学学报(英文版)》2002,17(1):85-92
This paper provides further contributions to the theory of linear sufficiency in the general Gauss-Markov model E(y)= Xt3, Var (y)= V. The notion of linear sufficiency introduced by Baksalary and Kala(1981) and Drygas(1983) is extended for any specific estimable function c‘β. Some general results with respect to the extended concept are obtained. An essential result concerning the former notion is a direct consequence of this paper. 相似文献
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半参数广义线性混合效应模型的影响分析 总被引:1,自引:1,他引:0
本文把随机效应当作是缺失数据并利用P-样条拟合非参数部分,从而得到了半参数广义线性混合效应模型(GPLMM)的MCNR估计算法;同时利用Q-函数,我们得到了模型的参数部分的广义Cook距离以及非参数部分的广义DFIT,此外,本文还研究了四种不同扰动情形的PLMM的局部影响分析,得到了相应的影响矩阵,最后,我们通过—个实际例子验证了所提出的诊断统计量的有效性。 相似文献
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本文对Cook(1986)提出的局部影响分析方法进行修正,找出它的不足之处,并提出用二阶导数准则来进行局部影响分析,这种方法可以推广到其它的似然估计问题中去,文中用Leukernia data和Finney's data来说明这种方法人成劣,并与一阶导数(斜率)的结果相比较,提出了有实际意义的诊断方法。 相似文献
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Local influence in multilevel regression for growth curves 总被引:1,自引:0,他引:1
Influence analysis is important in modelling and identification of special patterns in the data. It is well established in ordinary regression. However, analogous diagnostics are generally not available for the multilevel regression model, in which estimation involves a complex iterative algorithm. This paper studies the local influence of small perturbations on the parameter estimates in the multilevel regression model with application to growth curves. The estimation is based on the iterative generalized least-squares (IGLS) method suggested by Goldstein (Biometrika 73 (1986) 43). The generalized influence function and generalized Cook statistic (Biometrika 84(1) (1997) 175) of IGLS of unknown parameters under some specific simultaneous perturbations are derived to study the joint influence of subject units on parameter estimators. The perturbation scheme is introduced through a variance–covariance matrix of error variables. A one-step approximation formula is suggested for simplifying the computations. The method is examined on growth-curve data. 相似文献
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Jin-hong You Gemai Chen Min Chen Xue-lei JiangUniversity of Regina Regina Saskatchewan SS OA CanadaUniversity of Calgary Calgary Alberta TN N CanadaAcademy of Mathematics System Sciences Chinese Academy of Sciences Beijing China 《应用数学学报(英文版)》2003,19(3):363-370
Consider the partly linear regression model ,where yi's are responses, xi = (xi1, xi2,…,xip)' and ti ∈T are known and nonrandom design points, T is a compact set in the real line is an unknown parameter vector, g(·) is an unknown function and {Ei} isa linear process, i.e., random variables with zeromean and variance o2e. Drawing upon B-spline estimation of g(·) and least squares estimation of 0, we construct estimators of the autocovariances of {Ei}- The uniform strong convergence rate of these estimators to their true values is then established. These results not only are a compensation for those of [23], but also have some application in modeling error structure. When the errors {Ei} are an ARMA process, our result can be used to develop a consistent procedure for determining the order of the ARMA process and identifying the non-zero coefficients of the process. Moreover, our result can be used to construct the asymptotically efficient estimators for parameters in the ARMA error process. 相似文献
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Song Zhang & Dehui Wang 《数学研究通讯:英文版》2013,29(3):271-279
In this paper, we propose a log-normal linear model whose errors are
first-order correlated, and suggest a two-stage method for the efficient estimation of
the conditional mean of the response variable at the original scale. We obtain two
estimators which minimize the asymptotic mean squared error (MM) and the asymptotic bias (MB), respectively. Both the estimators are very easy to implement, and
simulation studies show that they are perform better. 相似文献
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观测向量的变换对广义线性模型参数估计的影响 总被引:1,自引:0,他引:1
本文一般地考察了观测向量Y用线性变换FY代替对广义线性模型Y=Xβ+ε的系数估计的影响,得到了由变换引起的方差增量公式,并由此得到了一个可估子空间,当且仅当其中元素的估计优良性不因观测向量的变化而改变,这一结果推广了文献[1]的结果. 相似文献
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In this paper, we give the representation of the best linear unbiased predictor(BLUP)of the new observations under M_r_f. Through the representation, we give necessary and sufficient conditions that the estimators, OLSEs(ordinary least squares estimators) and BLUEs(best linear unbiased estimators), under M_f and M_r_f, and the predictor, BLUP, under M_f continue to be the BLUP under M_r_f, respectively. 相似文献