multicollinearity

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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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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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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