C#實現最小二乘法
根據http://zh.wikipedia.org/wiki/%E6%9C%80%E5%B0%8F%E4%BA%8C%E4%B9%98%E6%B3%95裡面的說法:
線性函式模型
典型的一類函式模型是線性函式模型。最簡單的線性式是,寫成矩陣式,為
直接給出該式的引數解:
和
其中,為t值的算術平均值。也可解得如下形式:
b1為斜率,b0為截距,可以先根據x,y陣列,以及上面的公式先計算出斜率,再計算截距。
因為原來參考程式碼中,返回為一個數組,根據與原來程式碼的相容性,呼叫LinearResult(double[],double[])方法返回是一個數組。result[0]為斜率,result[1]為截距。
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class Linear
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{
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public double[] LinearResult(double[] arrayX, double[] arrayY)
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{
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double[] result = { 0, 0 };
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if (arrayX.Length == arrayY.Length)
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{
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double averX = arrayX.Average();
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double averY = arrayY.Average();
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result[0] = Scale(averX, averY, arrayX, arrayY);
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result[1] = Offset(result[0],averX,averY);
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}
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return result;
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}
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private double Scale(double averX, double averY, double[] arrayX, double[] arrayY)
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{
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double scale = 0;
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if (arrayX.Length == arrayY.Length)
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{
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double Molecular = 0;
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double Denominator = 0;
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for (int i = 0; i < arrayX.Length; i++)
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{
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Molecular += (arrayX[i] - averX) * (arrayY[i] - averY);
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Denominator += Math.Pow((arrayX[i] - averX), 2);
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}
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scale = Molecular / Denominator;
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}
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return scale;
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}
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private double Offset(double scale, double averX,double averY)
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{
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double offset = 0;
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offset = averY - scale * averX;
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return offset;
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}
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}
/// <summary> /// 計算一元一次方程係數(利用最小二乘法) /// 20200320新增 /// </summary> /// <param name="xValues"></param> /// <param name="yValues"></param> /// <returns></returns> private double[] CalCoefficientOfLinearEquation(double[] xValues, double[] yValues) { if (xValues.Length != yValues.Length) return null; int valCount = xValues.Length; //計算X2=∑(xi)^2 , X=∑ xi , Yx=∑(xi*yi) , Y=∑ yi double X2 = 0; double X = 0; double Yx = 0; double Y = 0; for (int i = 0; i < valCount; i++) { X2 += Math.Pow(xValues[i], 2); X += xValues[i]; Yx += xValues[i] * yValues[i]; Y += yValues[i]; } //計算線性方程係數y=ax+b double a = (Yx * valCount - X * Y) / (X2 * valCount - X * X); double b = (X2 * Y - Yx * X) / (X2 * valCount - X * X); //返回係數的陣列 double[] temp = new double[] { a, b }; return temp; }