Fits multiple linear equations to data.
Parameters |
Description |
B |
Returns regression coefficients for multiple linear function. |
X |
Vector of independent variable. |
Y |
Vector of dependent variable. |
Constant |
If true then intercept term b(0) will be included in calculations. If false, set intercept term b(0) to 0.0. |
Weights |
Weights (optional). Weights are used only if they are set. |
The routine fits equations to data by minimizing the sum of squared residuals. The observed values obey the following equation:
where X is matrix, Y, B are vectors.
In the following example we generate some data. Then we fit multiple linear function to this data and retreive it's regression coefficients.
#include "MtxExpr.hpp" #include "Math387.hpp" #include "RegModels.hpp" #include "MtxVecTee.hpp" void __fastcall Example(); { sMatrix X; sVector Y,B; X->SetIt(3,2,false,OPENARRAY(double,(1.0, 2.0, -3.2, 2.5, 8.0, -0.5))); Y->SetIt(false, OPENARRAY(double,(-3.0, 0.25, 9.0))); MulLinFit(B,X,Y,true,NULL); // B = (18.646428571, -1.9464285714, -9.85 ) }
Copyright (c) 1999-2024 by Dew Research. All rights reserved.
|
What do you think about this topic? Send feedback!
|