CRAN Package Check Results for Package fpca

Last updated on 2014-09-03 08:53:29.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2-1 0.59 58.05 58.64 OK
r-devel-linux-x86_64-debian-gcc 0.2-1 0.60 56.30 56.90 OK
r-devel-linux-x86_64-fedora-clang 0.2-1 125.24 NOTE
r-devel-linux-x86_64-fedora-gcc 0.2-1 114.55 NOTE
r-devel-osx-x86_64-clang 0.2-1 86.88 OK
r-devel-windows-ix86+x86_64 0.2-1 3.00 93.00 96.00 OK
r-patched-linux-x86_64 0.2-1 2.62 62.92 65.54 OK
r-patched-solaris-sparc 0.2-1 799.30 OK
r-patched-solaris-x86 0.2-1 138.90 OK
r-release-linux-ix86 0.2-1 0.96 80.86 81.82 OK
r-release-linux-x86_64 0.2-1 0.63 63.27 63.90 OK
r-release-osx-x86_64-mavericks 0.2-1 OK
r-release-windows-ix86+x86_64 0.2-1 3.00 110.00 113.00 OK
r-oldrel-windows-ix86+x86_64 0.2-1 2.00 91.00 93.00 OK

Check Details

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-fedora-clang, r-devel-linux-x86_64-fedora-gcc