Ridgecv

Ridgecv

Purpose

Ridge regression with cross validation.

Synopsis

[b,theta,cumpress] = ridgecv(x,y,thetamax,divs,split)

Description

This function calculates a ridge regression model using a matching set of predictor variables (x-block) x and predicted variables (y-block) y, and uses cross-validation to determine the optimum value of the ridge parameter theta. The maximum value of the ridge parameter to consider is given by thetamax (where 0 < thetamax).

Inputs

• x = matrix of independent variables
• y = matching vector of dependent variables
• thetamax = maximum value of ridge parameter theta to consider
• divs = the number of values of theta to test
• split = the number of times to split and test the data for cross-validation

Outputs

• b = the regression column vector, at the optimal ridge parameter value
• theta = the optimal ridge parameter value
• cumpress = Predicted Residual Sum of Squares (PRESS) statistics for the cross-validation

Note: RIDGECV uses the venetian blinds cross-validation method.

See Also

crossval, pcr, pls, analysis, ridge