文件名称:Least-squares-Curve-Fit-unit
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最小二乘是由方程式近似的数据点的一组的方式,让你预测中间值,或计算的数据的一些措施。您可能已经通过绘制通过数目的数据点图上绘制的直线近似的趋势线。最小二乘这不只是“装修”,但在数学的方式,最大限度地减少错误,从而导致。我的单元延伸最小二乘从仅仅是一种直线拟合到高阶多项式为更复杂的数据(其中可能有一平方律拟合的物理原因,例如),或更好的匹配的数据。-Least-squares is a way of approximating a set of data points by an equation, allowing you to predict intermediate values or calculate some measure of the data. You may have approximated a trend-line by drawing a straight line through a number of data points plotted on a graph. Least-squares does just this "fitting" but in a mathematical way that minimises the errors that result. My unit extends least-squares from just a straight-line fit into higher order polynomials for more complex data (where there may be a physical reason for a square-law fit, for example) or for a better match to the data.
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下载文件列表
Source\_Private
Source
PolyFitC++.zip
TestCurveFitForm.dfm
TestCurveFitForm.pas
TestCurveFit.cfg
TestCurveFit.dof
TestCurveFit.dpr
TestCurveFit.exe
TestCurveFit.res
CurveFit.txt
CurveFit.pas
TonyFoale.zip