It is necessary to make a reasonable covariance structure for longitudinal data so as to fit these data with linear or nonlinear models.
为了用线性或非线性模型拟合纵向数据，需要确定一个合理的协方差结构。
The results of PCA and DPC show that the sampling data have a remarkable nonlinear structure.
PCA和DPC分析结果表明，取样数据具有明显的非线性结构。
In this paper, the principle of nonlinear correction of data by using RBF neural network, the structure of neural network and the determination method of parameters are described.
介绍了利用RBF神经网络进行数据非线性校正的原理以及RBF神经网络结构和参数的确定方法。
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