Computes Cross-validated Error Sum of Squares for a Functional Regression Model
fRegress.CV
Language Reference for FDA Library

Computes Cross-validated Error Sum of Squares for a Functional Regression Model

DESCRIPTION:

For a functional regression model with a scalar dependent variable, a cross-validated error sum of squares is computed. This function aids the choice of smoothing parameters in this model using the cross-validated error sum of squares criterion.

USAGE:

fRegress.CV(yvec, xfdlist, betalist)

REQUIRED ARGUMENTS:

yvec
a vector of dependent variable values.
xfdlist
a list whose members are functional parameter objects specifying functional independent variables. Some of these may also be vectors specifying scalar independent variables.
betalist
a list containing functional parameter objects specifying the regression functions and their level of smoothing.

VALUE:

the sum of squared errors in predicting yvec.

SEE ALSO:

fRegress, fRegress.stderr

EXAMPLES:

See the analyses of the daily weather data.