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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The method involves principal components analysis, phase space reconstruction and least squares estimate.
方法包括3部分:主分量分析, 相空间重构,最小二乘拟合.
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The method seeks the solution of the nonlinear least squares estimate of partially observed values.
说明该方法的解一定是部分观测值的非线性最小二乘估计.
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