表明： 基于氨基酸组成和有偏自协方差函数为特征矢量的BP神经网络预测蛋白质二级结构含量的方法可有效提高预测精度。
It is shown that the BP neural network method combined with the amino-acid composition and the biased auto-covariance function features could effectively improve the prediction accuracy.
建立不完全数据回归方程，给出回归系数的最佳无偏整体估计及其协方差矩阵。
The regression equation for incomplete data is established, and the best unbiased integral estimators of the regression parameters and their covariance matrix are also given.
对两个参数各提出了一个无偏估计并采用协方差改进法分别对其作了改进。
Unbiased estimation for the two parameters of the special model is proposed and improved by covariance adjustment approach, separately.
应用推荐