View source for 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) <tt>x</tt> and predicted variables (y-block) <tt>y</tt>, and uses cross-validation to determine the optimum value of the ridge parameter <tt>theta</tt>.  The maximum value of the ridge parameter to consider is given by <tt>thetamax</tt> (where 0 < thetamax). 

====Inputs====

* '''x''' = matrix of independent variables
* '''y''' = matching vector of dependent variables
* '''thetamax''' = maximum value of ridge parameter <tt>theta</tt> to consider
* '''divs''' = the number of values of <tt>theta</tt> 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]]