在误差为相依的情况下，讨论了线性回归模型的刀切最小二乘估计与广义刀切最小二乘估计。

This paper studies linear regression models with dependent errors, and we introduce the jackknifed least squares estimator and generalized jackknife least squares estimator.

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比较分析了最小二乘支持向量机（LSSVM）和广义回归神经网络（GRNN）这两种方法的特点。

The features of two methods, i. e. least square support vector machine (LSSVM) and generalized regression neural network (GRNN) are compared and analyzed.

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