共查询到17条相似文献，搜索用时 53 毫秒
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一般广义岭估计的效率上界 总被引：2，自引：0，他引：2
考察一般Gauss-Markov模型中未知参数向量的最优线性无偏估计的改造问题,讨论了方兴等人提出的最优化无偏估计的一种估计的相对效率,把该文中给出的一般岭估计的相对效率的上界,推广到一般广义岭估计的相对效率的上界.yh 相似文献
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考虑了Gauss—Markov模型中未知参数向量p的最佳线性无偏估计的改进问题,对一般岭估计与BLUE进行了比较,给出了一般岭估计与BLUE的一种新的相对效率e,并导出了e的下界． 相似文献
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本文对线性回归模型给出了其参数β的广义岭估计优于LS估计的一个充分条件,从而把文献[1]中,岭估计优于LS估计的充分条件统一起来 相似文献
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考察一般Gauss-Markov模型中未知参数向量β的一般广义岭估计的优良性质。对最小二乘估计相对于一般广义岭估计效率的下界问题作进一步的探讨,得到其更优的下界． 相似文献
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广义岭估计的效率 总被引：3，自引：1，他引：2
王平华 《泉州师范学院学报》1998,16(2):13-15
本文讨论了Guass-Markov模型中未知参数的LSE^↑β的改进,引入了一种估计的相对效率,证明了广义岭估计比（狭义）岭估计的效率较高。 相似文献
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对一般线性模型中参数β的最小二乘估计和岭估进行了修正,把岭估计中各量的非均匀压缩修为均匀压缩,从而得到了β的一种均匀压缩估计βa,并给出了具体的求法和适用范围。 相似文献
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LSE相对于一般广义岭估计的效率下界 总被引：1，自引：0，他引：1
考察一般Gauss-Markov模型中未知参数向量β的估计的改造问题,进一步讨论了方兴等人提出的一种估计的相对效率,对其部分结果进行推广,得到LSE相对于一般广义岭估计的效率的下界. 相似文献
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考察一般Gauss-Markov模型中未知参数向量β的岭估计的优良性质,在文献[1]提出的估计(~β)相对于估计(^β)的(相对)效率e((~β)|(^β))下,进一步讨论了最小二乘估计(LSE)相对于岭估计的效率下界,得到更好的结果.证明了:当X呈病态时,采用些估计以损失无偏性来换取更小的均方误差是可取的. 相似文献
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估计量的优良性是回归模型中的重要内容.本文讨论了在Pitman准则下,岭估计与Stein压缩估计的优良性,得到了岭估计优于Stein压缩估计的一个充分条件. 相似文献
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文中首先将随机效应不同的线性混合模型转化为满足假设的线性模型.在此基础上,根据不同的情况,对其中的固定效应参数作最小二乘估计;当模型在较强的复共线性时,相应的对其做岭估计,并比较最小二乘估计与岭估计之间的优劣;当其中的随机变量之间并不独立时,通过对模型的变换,求出参数的广义最小二乘估计. 相似文献
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Ridge generalized least squares (RGLS) is a recently proposed estimation procedure for structural equation modeling. In the formulation of RGLS, there is a key element, ridge tuning parameter, whose value determines the efficiency of parameter estimates. This article aims to optimize RGLS by developing formulas for the ridge tuning parameter to yield the most efficient parameter estimates in practice. For the formulas to have a wide scope of applicability, they are calibrated using empirical efficiency and via many conditions on population distribution, sample size, number of variables, and model structure. Results show that RGLS with the tuning parameter determined by the formulas can substantially improve the efficiency of parameter estimates over commonly used procedures with real data being typically nonnormally distributed. 相似文献
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Shaun McQuitty 《Structural equation modeling》2013,20(3):244-252
LISREL 8 invokes a ridge option when maximum likelihood or generalized least squares are used to estimate a structural equation model with a nonpositive definite covariance or correlation matrix. The implications of the ridge option for model fit statistics, parameter estimates, and standard errors are explored through the use of 2 examples. The results indicate that maximum likelihood estimates are quite stable with the ridge option, though fit statistics and standard errors vary considerably and therefore cannot be trusted. As a result of these findings, the application of the ridge method to structural equation models is not recommended. 相似文献
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This article proposes 2 classes of ridge generalized least squares (GLS) procedures for structural equation modeling (SEM) with unknown population distributions. The weight matrix for the first class of ridge GLS is obtained by combining the sample fourth-order moment matrix with the identity matrix. The weight matrix for the second class is obtained by combining the sample fourth-order moment matrix with its diagonal matrix. Empirical results indicate that, with data from an unknown population distribution, parameter estimates by ridge GLS can be much more accurate than those by either GLS or normal-distribution-based maximum likelihood; and standard errors of the parameter estimates also become more accurate in predicting the empirical ones. Rescaled and adjusted statistics are proposed for overall model evaluation, and they also perform much better than the default statistic following from the GLS method. The use of the ridge GLS procedures is illustrated with a real data set. 相似文献
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Zijun Ke 《Structural equation modeling》2013,20(3):382-400
This study examined and compared various statistical methods for detecting individual differences in change. Considering 3 issues including test forms (specific vs. generalized), estimation procedures (constrained vs. unconstrained), and nonnormality, we evaluated 4 variance tests including the specific Wald variance test, the generalized Wald variance test, the specific likelihood ratio (LR) variance test, and the generalized LR variance test under both constrained and unconstrained estimation for both normal and nonnormal data. For the constrained estimation procedure, both the mixture distribution approach and the alpha correction approach were evaluated for their performance in dealing with the boundary problem. To deal with the nonnormality issue, we used the sandwich standard error (SE) estimator for the Wald tests and the Satorra–Bentler scaling correction for the LR tests. Simulation results revealed that testing a variance parameter and the associated covariances (generalized) had higher power than testing the variance solely (specific), unless the true covariances were zero. In addition, the variance tests under constrained estimation outperformed those under unconstrained estimation in terms of higher empirical power and better control of Type I error rates. Among all the studied tests, for both normal and nonnormal data, the robust generalized LR and Wald variance tests with the constrained estimation procedure were generally more powerful and had better Type I error rates for testing variance components than the other tests. Results from the comparisons between specific and generalized variance tests and between constrained and unconstrained estimation were discussed. 相似文献