Linear Model Analysis of Observational Data in the Sense of Least –Squares Criterion

J.A. Basabrain

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Linear Model Analysis of Observational Data in the Sense of Least –Squares Criterion

机译：最小二乘准则意义上的观测数据线性模型分析

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The present paper is devoted for the following goals: To develop an algorithm for model analysis of observational data in the sense of the least –squares criterion with full error analysis.. By this algorithm one computes, all the solutions with their variances, the variance of the fit, the average square distance between the least square solution and the exact solution, and graphical representation between the row and the fitted data. Mathematica module of the algorithm was established, through five points, its purpose –input - output –needed procedures and the list of the module. By this paper we have been tried to produce an error controlled algorithm of the least squares method for observational data.

机译：本文致力于以下目的：开发一种在最小二乘准则的意义下进行全误差分析的观测数据模型分析算法。通过这种算法，可以计算出所有具有方差的解，方差拟合度，最小二乘解与精确解之间的平均平方距离，以及行与拟合数据之间的图形表示。该算法的Mathematica模块通过五个方面建立了其目的-输入-输出-所需程序以及模块列表。通过本文，我们试图为观测数据产生最小二乘法的误差控制算法。

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《American Journal of Mathematical Analysis》 |2015年第2期|共7页
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J.A. Basabrain;
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Linear Model Analysis of Observational Data in the Sense of Least –Squares Criterion

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