最小二乘法在化工中广泛用于数据拟合的线性和非线性回归及模型参数估值。
The least square method is popularly used in linear and non-linear regressions for data fitting and estimating model parameters.
NLREG是一款强大地统计分析软件。能够进行线性和非线性回归分析，表面和曲线拟和。
NLREG is a powerful statistical analysis program that performs linear and nonlinear regression analysis, surface and curve fitting.
根据实测的数据，采用一元线性、多元线性和非线性回归进行拟合，得到34个红海榄幼苗主要形态因子和生物量的回归模型。
Based on the data observed, 34 regression models on the morphological variables and biomass of the seedlings were set up using linear, multilinear and non linear regression.
仿真和实算结果表明，对于一大类线性和非线性回归模型，该方法给出的回归模型的参数估计效率的估计更接近模型参数估计效率的真值。
Simulation results and real measuring data calculations show that the precision estimation efficiency can be obtained by our method for a large class of linear and nonlinear regression models.
支持向量机(SVM)是一种线性机器，广泛用于模式分类和非线性回归。
The support vector machine (SVM) is a linear classification machine, it is used commonly in the pattern recognition and nonlinear regression.
和普通的非线性回归模型一样，具有相关误差的非线性模型也存在异方差检验问题，但通常还要检验相关性。
As in ordinary regression models, the problem of the heteroscedasticity test still exists in nonlinear models with correlated errors, but, the test for correlation also needs to be considered.
结果表明，神经网络的预测效果比线性回归和简单的非线性回归有明显提高。
The Results show that the forecast value of ANN is clearly better than that of regression analysis method.
介绍非线性回归和操作条件的非线性优化方法。
The non linear regression and non linear optimization methods for operating conditions were introduced.
即把一元非线性回归和多元线性回归结合起来，构造一个混合回归模型，这样就减小了模型的残差平方和，从而提高预报的准确性。
We combine unitary nonlinear regression with multivariate linear regression, it can reduce the error sum of squares of the model and improve the precision of forecast.
数据拟合是数理统计学中的一个永恒话题，在实际工作中我们最常用的拟合方法是回归分析，其中包括线性回归和非线性回归。
Data smoothing is a perpetual topic in mathematical statistics. In practice we usually use regression to smooth data, including linear regression and nonlinear regression.
数据拟合是数理统计学中的一个永恒话题，在实际工作中我们最常用的拟合方法是回归分析，其中包括线性回归和非线性回归。
Data smoothing is a perpetual topic in mathematical statistics. In practice we usually use regression to smooth data, including linear regression and nonlinear regression.
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