Overload List
| # | Signature | Description |
|---|---|---|
| 1 | void MulLinRegress(TVec *Y, TMtx *A, TVec *b, bool Constant = true, TVec *YCalc = null, TMtx *ATA = null, TRegSolveMethod Method = TRegSolveMethod::regSolveLQR); | Multivariante linear regression. |
| 2 | void MulLinRegress(TVec *Y, TMtx *A, TVec *b, TVec *Weights, bool Constant = true, TVec *YCalc = null, TMtx *ATA = null, TRegSolveMethod Method = TRegSolveMethod::regSolveLQR); | Multivariante linear regression. |
Overload 1: void MulLinRegress(TVec *Y, TMtx *A, TVec *b, bool Constant = true, TVec *YCalc = null, TMtx *ATA = null, TRegSolveMethod Method = TRegSolveMethod::regSolveLQR);
Multivariante linear regression.
| # | Name | Type | Description |
|---|---|---|---|
| 1 | Y | TVec * | |
| 2 | A | TMtx * | |
| 3 | b | TVec * | |
| 4 | Constant = true | bool | |
| 5 | YCalc = null | TVec * | |
| 6 | ATA = null | TMtx * | |
| 7 | Method = TRegSolveMethod::regSolveLQR | TRegSolveMethod |
Declared in Dew::Stats::Units::Regress · Dew.Stats/Units.Regress.h · Cross-compiler
Overload 2: void MulLinRegress(TVec *Y, TMtx *A, TVec *b, TVec *Weights, bool Constant = true, TVec *YCalc = null, TMtx *ATA = null, TRegSolveMethod Method = TRegSolveMethod::regSolveLQR);
Multivariante linear regression.
| # | Name | Type | Description |
|---|---|---|---|
| 1 | Y | TVec * | Defines vector of dependant variable. |
| 2 | A | TMtx * | Defines matrix of independant (also X) variables. |
| 3 | b | TVec * | Returns calculated regression coefficiens. |
| 4 | Weights | TVec * | Defines weights (optional). |
| 5 | Constant = true | bool | If true then intercept term b(0) will be included in calculations. If false, set intercept term b(0) to 0.0. |
| 6 | YCalc = null | TVec * | Returns vector of calculated dependant variable, where YCalc = A*b. |
| 7 | ATA = null | TMtx * | Returns inverse matrix of normal equations i.e [A(T)*A]^-1. |
| 8 | Method = TRegSolveMethod::regSolveLQR | TRegSolveMethod | Use QR, SVD, or LU solver. Typically QR will yield best compromise between stability and performance. |
Remarks:
Routine fits equations to data by minimizing the sum of squared residuals:
SS = Sum [y(k) - ycalc(k)]^2 ,
where y(k) and ycalc(k) are respectively the observed and calculated value of the dependent variable for observation k. ycalc(k) is a function of the regression parameters b(0), b(1) ... Here the observed values obey the following equation:
y(k) = b(0) + b(1) * x(1,k) + b(2) * x(2,k) + ...
i.e
y = A * b.
To calculate additional regression statistical values, use Regress::RegressTest routine.
Declared in Dew::Stats::Units::Regress · Dew.Stats/Units.Regress.h · Cross-compiler