Last updated on 2020-08-07 01:50:23 CEST.
| Package | NOTE |
|---|---|
| fpca | 12 |
Current CRAN status:
Version: 0.2-1
Check: DESCRIPTION meta-information
Result: NOTE
Malformed Description field: should contain one or more complete sentences.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64
Version: 0.2-1
Check: R code for possible problems
Result: NOTE
GenObs: no visible global function definition for 'rnorm'
GenObs.T: no visible global function definition for 'rt'
MeasL: no visible global function definition for 'rbeta'
OutDet: no visible global function definition for 'median'
RanCur: no visible global function definition for 'rnorm'
init: no visible global function definition for 'prcomp'
Undefined global functions or variables:
median prcomp rbeta rnorm rt
Consider adding
importFrom("stats", "median", "prcomp", "rbeta", "rnorm", "rt")
to your NAMESPACE file.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-x86, r-release-linux-x86_64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64
Version: 0.2-1
Check: Rd line widths
Result: NOTE
Rd file 'fpca.mle.Rd':
\usage lines wider than 90 characters:
fpca.mle(data.m, M.set,r.set, ini.method="EM", basis.method="bs", sl.v=rep(0.5,10), max.step=50,
\examples lines wider than 100 characters:
##model selection result: the true model M=5, r=3 is selected with the smallest CV score among all converged models
##look at the CV scores and convergence for each model: note that model (M=5, r=4) does not converge.
#get predicted trajectories on a fine grid: the same grid for which mean and eigenfunctions are evaluated
plot(t.c,y.c,ylim=range(pred[,id]),xlab="time",ylab="obs", main=paste("predicted trajectory of curve", id))
##model selection result: the true model M=5, r=3 is selected with the smallest CV score among all converged models
plot(grids.new,result$eigenfunctions[i,],ylim=range(result$eigenfunctions),xlab="time",ylab=paste("eigenfunction",i))
##look at the CV scores and convergence for each model: note that model (M=5, r=4) does not converge.
These lines will be truncated in the PDF manual.
Flavors: r-devel-linux-x86_64-debian-clang, r-devel-linux-x86_64-debian-gcc, r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-patched-linux-x86_64, r-release-linux-x86_64