Dew Stats for .NET
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Principal Component Regression.
Parameters |
Description |
[In] TVec Y |
Defines vector of dependant variable. |
[In] TMtx A |
Defines matrix of independant variables. |
[In] TVec b |
Returns calculated regression coefficiens. |
[In] TVec YCalc |
Returns vector of calculated dependant variable, where YCalc = A*b + constant term. |
[In] TVec Bse |
Returns principal component b coefficient standard error. |
int NumOmmit |
Defines the number of variables to ommit from initial model. |
Performs unweighted Principal Component Regression (PCR). PCR is a technique for analyzing multiple regression data that suffer from multicollinearity. When multicollinearity occurs, least squares estimates are unbiased, but their variances are large so they may be far from the true value. By adding a degree of bias to the regression estimates, principal components regression reduces the standard errors. The algorithm first standardizes A matrix and performs PC regression on standardized matrix.
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