lambda2gcv: Compute GCV Criterion

In fda: Functional Data Analysis

Compute GCV Criterion

Description

The generalized cross-validation or GCV criterion is often used to select an appropriate smoothing parameter value, by finding the smoothing parameter that minimizes GCV. This function locates that value.

Usage

  lambda2gcv(log10lambda, argvals, y, fdParobj, wtvec=rep(1,length(argvals)))

Arguments

log10lambda	the logarithm (base 10) of the smoothing parameter
argvals	a vector of argument values.
y	the data to be smoothed.
fdParobj	a functional parameter object defining the smooth.
wtvec	a weight vector used in the smoothing.

Details

Currently, lambda2gcv

Value

1. fdParobj[['lambda']] <- 10^log10lambda

2. smoothlist <- smooth.basks(argvals, y, fdParobj, wtvec)

3. return(smoothlist[['gcv']])

References

Ramsay, James O., Hooker, Giles, and Graves, Spencer (2009), Functional data analysis with R and Matlab, Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2005), Functional Data Analysis, 2nd ed., Springer, New York.

Ramsay, James O., and Silverman, Bernard W. (2002), Applied Functional Data Analysis, Springer, New York.

See Also

smooth.basis fdPar

fda documentation built on Sept. 30, 2024, 9:19 a.m.