CRAN Package Check Results for Package fpca

Last updated on 2014-04-16 15:49:27.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.2-1 0.66 66.68 67.34 OK
r-devel-linux-x86_64-debian-gcc 0.2-1 0.66 65.16 65.82 OK
r-devel-linux-x86_64-fedora-clang 0.2-1 136.14 NOTE
r-devel-linux-x86_64-fedora-gcc 0.2-1 132.78 NOTE
r-devel-macosx-x86_64-clang 0.2-1 95.35 OK
r-devel-macosx-x86_64-gcc 0.2-1 OK
r-devel-windows-ix86+x86_64 0.2-1 3.00 102.00 105.00 OK
r-patched-linux-x86_64 0.2-1 0.66 65.07 65.73 OK
r-patched-solaris-sparc 0.2-1 792.10 OK
r-patched-solaris-x86 0.2-1 138.60 OK
r-release-linux-ix86 0.2-1 2.00 101.00 103.00 OK
r-release-linux-x86_64 0.2-1 0.65 66.06 66.71 OK
r-release-windows-ix86+x86_64 0.2-1 2.00 94.00 96.00 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