principal curve component

基本解释

This second edition has been completely revised to feature new chapters on principal component analysis, self-modeling curve resolution, and multi-way analysis methods.
这次再版已经被完全修正成特徵关于主成分分析，自我模型化曲线决定和多模式的分析方法的新章。
Experimental results show that principal curve component analysis is excellent for solving nonlinear principal component problem, and it has great applications potentials.
仿真实验结果表明，主曲线成分分析能很好地解决非线性主成分问题，应用前景广阔。
This paper considers the classification compression principal component estimate of regression coefficient in growth curve model and proves that it is superior to least squares estimate.
研究岭型主成分估计在降维估计类中的方差最优性，证明了它的方差阵在降维估计类中最小，方差阵的特征值最小，方差和及方差积最小。

主曲线成分
In this paper, a new nonlinear analytic method, principal curve component analysis (PC~2A) is proposed.
为此在对线性主成分分析非线性数据研究的基础上,提出了一种新的非线性成分分析方法,即主曲线成分分析。