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.
lambda2gcv(log10lambda, argvals, y, fdParobj, wtvec=rep(1,length(argvals)))1. \(fdParobj[['lambda']] <- 10^log10lambda\)
2. smoothlist <- smooth.basks(argvals, y, fdParobj, wtvec)
3. return(smoothlist[['gcv']])
the logarithm (base 10) of the smoothing parameter
a vector of argument values.
the data to be smoothed.
a functional parameter object defining the smooth.
a weight vector used in the smoothing.
Currently, lambda2gcv
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.
smooth.basis
fdPar