According to the economic indices of recent years, this paper constructs an econometric model of civil automobile by linear regression method and does some estimating and forecasting.
本文根据近年来国内各项经济指标，运用线性回归方法建立了民用汽车需求的计量经济模型，并对模型进行评价和预测。
The multiple linear regression model for forecasting the electricity demand and factors affecting it was established consequently and was optimized by regression tests.
建立了用电需求量与主要影响因素之间的多元线性回归预测模型，经过回归检验，确定了优化的多元线性回归预测模型。
Based on these, multiple linear regression, LMBP, MOBP, VLBP and BRBP model are used to forecast oil-gas prospecting cost, and each of their forecasting performances is compared.
在此基础上，采用了多元线性回归模型、LMBP模型、MOBP模型、VLBP模型与BRBP模型对油气勘探成本进行预测，并对各模型的预测性能进行了比对。
In first the linear regression model resulted from least square method is presented and its disadvantage is analyse, great forecasting error exists when extreme abnormal case exists.
本文先介绍了用最小二乘法进行线性回归预测的方法，并分析了其不足，即当存在着极端的异常情况时，往往存在着较大的预测误差。
In first the linear regression model resulted from least square method is presented and its disadvantage is analyse, great forecasting error exists when extreme abnormal case exists.
本文先介绍了用最小二乘法进行线性回归预测的方法，并分析了其不足，即当存在着极端的异常情况时，往往存在着较大的预测误差。
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