Re-run GSLCCA with different amounts of smoothing at the subject level prior to analysis.
a vector of integers specifying the number of SVD roots use when smoothing the data
This function can be used to investigate the effect of smoothing on GSLCCA.
subject.smooth argument of
gslcca is an
integer, the data matrix for each subject is approximated using the
corresponding number of SVD roots.
An object of class
"varySmooth" which is a list of
"gslcca" objects obtained by re-running the original GSLCCA
x with each value of
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
data(clonidine) ### Smoothed data - automatically select number of roots result <- gslcca(spectra, "Critical Exponential", time = Time, treatment = Treatment, subject.smooth = TRUE, data = clonidine, subset = Rat == "42") ### Vary number of roots multiRoots <- varySmooth(result, 2:15) ## plot optimised value plot(multiRoots, "opt") ## plot fitted values plot(multiRoots, "fitted") ## plot signature plot(multiRoots, "signature")
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