Round-off error, blind faith, and the powers that be: a caution on numerical error in coefficients for polynomial curves fit to psychophysical data.

Journal of outcome measurement Pub Date : 1998-01-01
V J Samar, C L De Filippo
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Abstract

Graphing and statistics software often permits users to fit polynomial curves, like a parabola or sigmoid, to scatter plots of psychophysical data points. These programs typically calculate the curve using double- or extended-precision numerical algorithms and display the resulting curve overlaid graphically on the scatter plot, but they may simultaneously display the equation that generates that curve with numerical coefficients that have been rounded off to only a few decimal places. If this equation is used for experimental or clinical applications, the round-off error, especially on coefficients for the higher powers, can produce anomalous findings due to systematic and extreme distortions of the fitted curve, even artifactually reversing the algebraic sign of the true slope of the fitted curve at particular data points. Care must be exercised in setting round-off criteria for coefficients of polynomial terms in curve-fit equations to avoid nonsensical measurement and prediction.

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四舍五入误差,盲目信仰,和权力:对拟合心理物理数据的多项式曲线系数的数值误差的警告。
绘图和统计软件通常允许用户拟合多项式曲线,如抛物线或s形曲线,以分散心理物理数据点。这些程序通常使用双精度或扩展精度数值算法计算曲线,并在散点图上以图形方式显示结果曲线,但它们可能同时显示生成该曲线的方程,其中的数值系数已四舍五入到小数位数。如果将该方程用于实验或临床应用,那么由于拟合曲线的系统性和极端扭曲,特别是系数的舍入误差,可能会产生异常结果,甚至人为地逆转拟合曲线在特定数据点的真实斜率的代数符号。在设定曲线拟合方程中多项式项系数的舍入准则时必须小心,以避免无意义的测量和预测。
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