CRAN Package Check Results for Package CoxBoost

Last updated on 2014-11-01 05:48:49.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.4 3.70 40.64 44.33 NOTE
r-devel-linux-x86_64-debian-gcc 1.4 3.62 39.14 42.76 NOTE
r-devel-linux-x86_64-fedora-clang 1.4 103.27 NOTE
r-devel-linux-x86_64-fedora-gcc 1.4 95.90 NOTE
r-devel-osx-x86_64-clang 1.4 85.03 NOTE
r-devel-windows-ix86+x86_64 1.4 11.00 75.00 86.00 NOTE
r-patched-linux-x86_64 1.4 3.88 41.31 45.18 NOTE
r-patched-solaris-sparc 1.4 560.80 NOTE
r-patched-solaris-x86 1.4 135.50 NOTE
r-release-linux-ix86 1.4 4.92 53.96 58.87 NOTE
r-release-linux-x86_64 1.4 4.02 42.84 46.86 NOTE
r-release-osx-x86_64-mavericks 1.4 NOTE
r-release-windows-ix86+x86_64 1.4 12.00 83.00 95.00 NOTE
r-oldrel-windows-ix86+x86_64 1.4 11.00 75.00 86.00 NOTE

Check Details

Version: 1.4
Check: top-level files
Result: NOTE
    Non-standard file/directory found at top level:
     ‘changeLog’
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

Version: 1.4
Check: dependencies in R code
Result: NOTE
    Packages in Depends field not imported from:
     ‘Matrix’ ‘prodlim’
     These packages need to be imported from (in the NAMESPACE file)
     for when this namespace is loaded but not attached.
    See the information on DESCRIPTION files in the chapter ‘Creating R
    packages’ of the ‘Writing R Extensions’ 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-devel-osx-x86_64-clang, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86, r-release-linux-ix86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64, r-oldrel-windows-ix86+x86_64

Version: 1.4
Check: foreign function calls
Result: NOTE
    Calls with DUP:
     .C("find_best01", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best", x.double.vec, as.integer(n), as.integer(p), uncens.C,
     as.integer(length(uncens)), as.double(actual.beta), as.double(actual.risk.score),
     as.double(actual.linear.predictor), weight.double.vec, max.nz.vec,
     max.1.vec, as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     as.double(penalty), as.integer(criterion == "pscore" || criterion ==
     "hpscore"), warncount = integer(1), min.index = integer(1),
     min.deviance = double(1), min.beta.delta = double(1), score.vec = double(p),
     DUP = FALSE, NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore" || criterion == "hpscore"),
     as.integer(presel.index - 1), as.integer(length(presel.index)),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore"), as.integer(new.candidates -
     1), as.integer(length(new.candidates)), warncount = integer(1),
     min.index = integer(1), min.deviance = double(1), min.beta.delta = double(1),
     score.vec = double(p), DUP = FALSE, NAOK = TRUE)
     .C("get_I_vec", as.double(x[subset.time.order, pen.index[I.index]]),
     as.integer(n), as.integer(length(I.index)), as.integer(length(uncens)),
     as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     I.vec = double(length(I.index)), DUP = FALSE)
    DUP is no longer supported and will be ignored.
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-osx-x86_64-clang, r-devel-windows-ix86+x86_64

Version: 1.4
Check: R code for possible problems
Result: NOTE
    CoxBoost: no visible global function definition for ‘Matrix’
    cv.CoxBoost: no visible global function definition for ‘mclapply’
    estimPVal: no visible global function definition for ‘mclapply’
    iCoxBoost: no visible global function definition for ‘Matrix’
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-osx-x86_64-clang, r-devel-windows-ix86+x86_64, r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86

Version: 1.4
Check: foreign function calls
Result: NOTE
    Calls with DUP != TRUE:
     .C("find_best01", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best", x.double.vec, as.integer(n), as.integer(p), uncens.C,
     as.integer(length(uncens)), as.double(actual.beta), as.double(actual.risk.score),
     as.double(actual.linear.predictor), weight.double.vec, max.nz.vec,
     max.1.vec, as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     as.double(penalty), as.integer(criterion == "pscore" || criterion ==
     "hpscore"), warncount = integer(1), min.index = integer(1),
     min.deviance = double(1), min.beta.delta = double(1), score.vec = double(p),
     DUP = FALSE, NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore" || criterion == "hpscore"),
     as.integer(presel.index - 1), as.integer(length(presel.index)),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore"), as.integer(new.candidates -
     1), as.integer(length(new.candidates)), warncount = integer(1),
     min.index = integer(1), min.deviance = double(1), min.beta.delta = double(1),
     score.vec = double(p), DUP = FALSE, NAOK = TRUE)
     .C("get_I_vec", as.double(x[subset.time.order, pen.index[I.index]]),
     as.integer(n), as.integer(length(I.index)), as.integer(length(uncens)),
     as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     I.vec = double(length(I.index)), DUP = FALSE)
    DUP = FALSE is deprecated and will be disabled in future versions of R.
Flavors: r-patched-linux-x86_64, r-patched-solaris-sparc, r-patched-solaris-x86

Version: 1.4
Check: foreign function calls
Result: NOTE
    Calls with DUP = FALSE:
     .C("find_best01", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best", x.double.vec, as.integer(n), as.integer(p), uncens.C,
     as.integer(length(uncens)), as.double(actual.beta), as.double(actual.risk.score),
     as.double(actual.linear.predictor), weight.double.vec, max.nz.vec,
     max.1.vec, as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     as.double(penalty), as.integer(criterion == "pscore" || criterion ==
     "hpscore"), warncount = integer(1), min.index = integer(1),
     min.deviance = double(1), min.beta.delta = double(1), score.vec = double(p),
     DUP = FALSE, NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore" || criterion == "hpscore"),
     as.integer(presel.index - 1), as.integer(length(presel.index)),
     warncount = integer(1), min.index = integer(1), min.deviance = double(1),
     min.beta.delta = double(1), score.vec = double(p), DUP = FALSE,
     NAOK = TRUE)
     .C("find_best_candidate", x.double.vec, as.integer(n), as.integer(p),
     uncens.C, as.integer(length(uncens)), as.double(actual.beta),
     as.double(actual.risk.score), as.double(actual.linear.predictor),
     weight.double.vec, max.nz.vec, max.1.vec, as.double(weightmat.times.risk),
     as.double(weightmat.times.risk.sum), as.double(penalty),
     as.integer(criterion == "pscore"), as.integer(new.candidates -
     1), as.integer(length(new.candidates)), warncount = integer(1),
     min.index = integer(1), min.deviance = double(1), min.beta.delta = double(1),
     score.vec = double(p), DUP = FALSE, NAOK = TRUE)
     .C("get_I_vec", as.double(x[subset.time.order, pen.index[I.index]]),
     as.integer(n), as.integer(length(I.index)), as.integer(length(uncens)),
     as.double(weightmat.times.risk), as.double(weightmat.times.risk.sum),
     I.vec = double(length(I.index)), DUP = FALSE)
    DUP = FALSE is deprecated and may be disabled in future versions of R.
Flavors: r-release-linux-ix86, r-release-linux-x86_64, r-release-osx-x86_64-mavericks, r-release-windows-ix86+x86_64