共查询到18条相似文献,搜索用时 125 毫秒
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本文对具有 p 个方差分量的线性模型讨论了方差分量线性函数的 Bayes 不变二次估计问题,给出了 Bayes 不变二次估计(无偏和有偏)的显示表达式,并且证明了它们在各自考虑的类中形成了可容许估计的完全类.在可容许估计的完全类中,还讨论了非负参数函数的非负估计问题,给出了可容许的非负定估计存在的充要条件. 相似文献
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方差分量的广义谱分解估计 总被引:9,自引:1,他引:8
对于随机效应部分为一般平衡多向分类的线性混合模型,将王松桂(2002)提出的一种称之为谱分解估计的参数估计新方法推广到随机效应设计阵为任意矩阵的含两个方差分量的线性混合模型,给出了方差分量的广义谱分解估计方法,并证明了所得估计的一些统计性质。另外,还就广义谱分解估计类中某些特殊估计和对应的方差分析估计进行了比较,得到了它们相等的充分必要条件。 相似文献
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本文研究了带有两个方差分量矩阵的多元线性混合模型方差分量矩阵的估计问题.对于平衡模型,给出了基于谱分解估计的一个方差分量矩阵的非负估计类.对于非平衡模型,给出了方差分量矩阵的广义谱分解估计类,讨论了与ANOVA估计等价的充要条件.同时,在广义谱分解估计的基础上给出了一种非负估计类,并讨论了其优良性.当具有较小二次风险的非负估计不存在时,从估计为非负的概率的角度考虑,将Kelly和Mathew(1993)提出的构造具有更小取负值概率的估计类的方法推广到本文的多元模型下,给出了较谱分解估计相比有更小取负值概率和更小风险的估计类.最后,模拟研究和实例分析表明文中理论结果有很好的表现. 相似文献
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线性混合模型中方差分量的ANOVA估计的改进 总被引:2,自引:0,他引:2
讨论了在含三个方差分量的线性混合模型中,在均方误差意义下,方差分量的方差分析估计的改进,并把这一结果推广到一般的线性混合模型上,得到一个改进方差分析估计的简单方法. 相似文献
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本文首先研究了含三个方差分量的线性混合随机效应模型改进的ANOVA估计, 此估计在均方损失下一致优于ANOVA估计. 由于这些方差估计取负值的概率大于零, 对得到的估计在某非负点采用截尾的方法得到非负估计是一种常用的方法. 对文章中提出的估计, 研究了此估计在某非负点截尾之后得到的估计在均方损失意义下优于截尾之前的估计的充分条件, 同时给出ANOVA估计在截尾之后优于它本身的充分条件, 而且将得到的结论推广到更一般的线性混合随机效应模型. 相似文献
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在线性混合效应模型下, 方差分析(ANOVA) 估计和谱分解(SD) 估计对构造精确检验和广义P-值枢轴量起着非常重要的作用. 尽管这两估计分别基于不同的方法, 但它们共享许多类似的优点, 如无偏性和有精确的表达式等. 本文借助于已得到的协方差阵的谱分解结果, 揭示了平衡数据一般线性混合效应模型下ANOVA 估计与SD 估计的关系, 并分别针对协方差阵两种结构: 套结构和多项分类随机效应结构, 给出了ANOVA 估计与SD 估计等价的充分必要条件. 相似文献
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Yuzo Maruyama William E. Strawderman 《Annals of the Institute of Statistical Mathematics》2005,57(1):157-165
This paper develops necessary conditions for an estimator to dominate the James-Stein estimator and hence the James-Stein
positive-part estimator. The ultimate goal is to find classes of such dominating estimators which are admissible. While there
are a number of results giving classes of estimators dominating the James-Stein estimator, the only admissible estimator known
to dominate the James-Stein estimator is the generalized Bayes estimator relative to the fundamental harmonic function in
three and higher dimension. The prior was suggested by Stein and the domination result is due to Kubokawa. Shao and Strawderman
gave a class of estimators dominating the James-Stein positive-part estimator but were unable to demonstrate admissiblity
of any in their class. Maruyama, following a suggestion of Stein, has studied generalized Bayes estimators which are members
of a point mass at zero and a prior similar to the harmonic prior. He finds a subclass which is minimax and admissible but
is unable to show that any in his class with positive point mass at zero dominate the James-Stein estimator. The results in
this paper show that a subclass of Maruyama's procedures including the class that Stein conjectured might contain members
dominating the James-Stein estimator cannot dominate the James-Stein estimator. We also show that under reasonable conditions,
the “constant” in shrinkage factor must approachp-2 for domination to hold. 相似文献
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Nityananda Sarkar 《Annals of the Institute of Statistical Mathematics》1989,41(4):717-724
In this paper we deal with comparisons among several estimators available in situations of multicollinearity (e.g., the r-k class estimator proposed by Baye and Parker, the ordinary ridge regression (ORR) estimator, the principal components regression (PCR) estimator and also the ordinary least squares (OLS) estimator) for a misspecified linear model where misspecification is due to omission of some relevant explanatory variables. These comparisons are made in terms of the mean square error (mse) of the estimators of regression coefficients as well as of the predictor of the conditional mean of the dependent variable. It is found that under the same conditions as in the true model, the superiority of the r-k class estimator over the ORR, PCR and OLS estimators and those of the ORR and PCR estimators over the OLS estimator remain unchanged in the misspecified model. Only in the case of comparison between the ORR and PCR estimators, no definite conclusion regarding the mse dominance of one over the other in the misspecified model can be drawn. 相似文献
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Adaptive Unified Biased Estimators of Parameters in Linear Model 总被引:1,自引:0,他引:1
HuYang Li-xingZhu 《应用数学学报(英文版)》2004,20(3):425-432
To tackle multi collinearity or ill-conditioned design matrices in linear models,adaptive biasedestimators such as the time-honored Stein estimator,the ridge and the principal component estimators havebeen studied intensively.To study when a biased estimator uniformly outperforms the least squares estimator,some sufficient conditions are proposed in the literature.In this paper,we propose a unified framework toformulate a class of adaptive biased estimators.This class includes all existing biased estimators and some newones.A sufficient condition for outperforming the least squares estimator is proposed.In terms of selectingparameters in the condition,we can obtain all double-type conditions in the literature. 相似文献
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We consider the estimation of error variance in the analysis of experiments using two level orthogonal arrays. We address
the estimator which is the minimum of all the estimators which we obtain by pooling some sums of squares for factorial effects.
Under squared error loss, we discuss whether or not this estimator uniformly improves upon the best positive multiple of error
sum of squares. We show that when we have two factorial effects, we obtain uniform improvement. However, we show that when
we have more than two factorial effects, we cannot necessarily obtain uniform improvement. Further, the above results are
applied to the problem of estimating the smallest scale parameter of chi-square distributions. 相似文献
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In this paper, we study the existence of the uniformly minimum risk equivariant (UMRE) estimators of parameters in a class
of normal linear models, which include the normal variance components model, the growth curve model, the extended growth curve
model, and the seemingly unrelated regression equations model, and so on. The necessary and sufficient conditions are given
for the existence of UMRE estimators of the estimable linear functions of regression coefficients, the covariance matrixV and (trV)α, where α > 0 is known, in the models under an affine group of transformations for quadratic losses and matrix losses, respectively.
Under the (extended) growth curve model and the seemingly unrelated regression equations model, the conclusions given in literature
for estimating regression coefficients can be derived by applying the general results in this paper, and the sufficient conditions
for non-existence of UMRE estimators ofV and tr(V) are expanded to be necessary and sufficient conditions. In addition, the necessary and sufficient conditions that there
exist UMRE estimators of parameters in the variance components model are obtained for the first time. 相似文献