multicollinearity

Both theoretical and computational results demonstrate that the PR estimator is a effective biased estimator for overcoming the effect of multicollinearity and is superior to the ordinary ridge estimator.

理论分析与计算结果表明，对于克服设计阵的复共线性对参数估计危害，部分岭估计是一种有针对性的有偏估计，它明显优于普通岭估计。

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Biased estimator based on diagnosis and measure of Multicollinearity

基于复共线性诊断和度量的有偏估计

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Properly selecting parameters to avoid stronger multicollinearity is a key to efficient estimation of parameters.

合理地选择参数，避免参数间的强复共线性，是参数有效估计的关键之一。

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Especially, the advantages of the method are marked, while the variables Xs multicollinearity being serious.

特别，当变量X多重相关性突出时，本文方法效果显著。

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The parameter estimation problem in linear model is considered when multicollinearity and outliers exist simultaneously.

本文讨论复共线性和粗差同时存在时线性模型的参数估计问题.

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The least Square estimates are not reliable when there exists multicollinearity in adjustment model.

当平差模型中存在复共线关系时,未知参数的最小二乘估计很不可靠.

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Result indicates that Fuzzy Principal Component Method can improve multicollinearity of Least Squares Estimate.

结果表明,这种方法改善了最小二乘回归中的多重共线性问题,具有实用价值.

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