fRegress.CV

yvec

a list whose members are functional parameter objects
specifying functional independent variables.  Some
of these may also be vectors specifying scalar independent
variables.

xfdlist

a list containing functional parameter objects specifying the
regression functions and their level of smoothing.

betalist

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.

smooth

These functions were developed to support 
   functional data analysis as described in Ramsay, J. O.
   and Silverman, B. W. (2005) Functional Data Analysis.
   New York: Springer.  They were ported from earlier
   versions in Matlab and S-PLUS.  A manual that describes
   the use of these functions is available in this
   library. The library also contains a number of the
   data sets used in the book along with R code for the
   analyses that produced many of the figures in the book.

fRegress.CV: Computes Cross-validated Error Sum of Squares for a Functional Regression Model

Description

Usage

Arguments

Value

See Also

Examples