CRAN Package Check Results for Package dse

Last updated on 2014-10-26 05:47:14.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2013.3-2 5.30 67.20 72.50 NOTE
r-devel-linux-x86_64-debian-gcc 2013.3-2 5.28 66.03 71.32 NOTE
r-devel-linux-x86_64-fedora-clang 2013.3-2 147.68 NOTE
r-devel-linux-x86_64-fedora-gcc 2013.3-2 134.56 NOTE
r-devel-osx-x86_64-clang 2013.3-2 123.10 NOTE
r-devel-windows-ix86+x86_64 2013.3-2 15.00 126.00 141.00 NOTE
r-patched-linux-x86_64 2013.3-2 5.33 73.28 78.61 NOTE
r-patched-solaris-sparc 2013.3-2 808.30 NOTE --no-tests
r-patched-solaris-x86 2013.3-2 183.90 NOTE
r-release-linux-ix86 2013.3-2 9.46 87.94 97.39 NOTE
r-release-linux-x86_64 2013.3-2 6.95 74.85 81.80 NOTE
r-release-osx-x86_64-mavericks 2013.3-2 NOTE
r-release-osx-x86_64-snowleopard 2013.3-2 NOTE
r-release-windows-ix86+x86_64 2013.3-2 13.00 129.00 142.00 NOTE
r-oldrel-windows-ix86+x86_64 2013.3-2 14.00 149.00 163.00 NOTE

Check Details

Version: 2013.3-2
Check: top-level files
Result: NOTE
    Non-standard file/directory found at top level:
     ‘src-c’
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: 2013.3-2
Check: dependencies in R code
Result: NOTE
    'library' or 'require' call to ‘setRNG’ which was already attached by Depends.
     Please remove these calls from your code.
    Package in Depends field not imported from: ‘setRNG’
     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-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: 2013.3-2
Check: foreign function calls
Result: NOTE
    Calls with DUP:
     .Fortran("datepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), as.integer(p), predictT = as.integer(TT),
     err, DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(model$A)[1]),
     as.integer(dim(model$B)[1]), as.integer(dim(C)[1]), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$A, model$B, C, TREND, as.integer(is), matrix(double(1),
     is, is), matrix(double(1), is, is), double(is), integer(is *
     is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(n), as.integer(p), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$F, G, model$H, K, Q, R, as.integer(gain), z, P, as.integer(IS),
     matrix(double(1), IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), n, n), matrix(double(1), p,
     p), rep(double(1), IS), rep(double(1), IS), rep(double(1),
     IS), integer(IS * IS), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(obj$A)[1]),
     as.integer(dim(obj$B)[1]), as.integer(dim(C)[1]), as.integer(TT),
     u, outputData(data), obj$A, obj$B, C, TREND, as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = matrix(double(1), TT,
     p), as.integer(m), as.integer(n), as.integer(p), as.integer(TT),
     u, outputData(data), obj$F, G, obj$H, K, Q, R, as.integer(gain),
     z, P, as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("arma", pred = matrix(1e+20, predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(m), as.integer(p), as.integer(dim(A)[1]), as.integer(dim(B)[1]),
     as.integer(dim(C)[1]), sampleT = as.integer(sampleT), predictT = as.integer(predictT),
     as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(A)) A else as.double(A),
     if (is.double(B)) B else as.double(B), if (is.double(C)) C else as.double(C),
     if (is.double(TREND)) TREND else as.double(TREND), as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kf", pred = matrix(double(1), predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(return.state), state = state, as.integer(return.track &
     !Innov), track = if (is.double(track)) track else as.double(track),
     as.integer(m), as.integer(n), as.integer(p), sampleT = as.integer(sampleT),
     predictT = as.integer(predictT), as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(Innov),
     if (is.double(z)) z else as.double(z), if (is.double(P)) P else as.double(P),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("simrma", y = if (is.double(y)) y else as.double(y),
     if (is.double(y0)) y0 else as.double(y0), as.integer(m),
     as.integer(p), as.integer(a), as.integer(b), as.integer(cc),
     as.integer(sampleT), as.double(input[1:sampleT, ]), if (is.double(input0)) input0 else as.double(input0),
     if (is.double(noise$w)) noise$w else as.double(noise$w),
     if (is.double(noise$w0)) noise$w0 else as.double(noise$w0),
     if (is.double(A)) A else as.double(A), if (is.double(B)) B else as.double(B),
     if (is.double(C)) C else as.double(C), if (is.double(TREND)) TREND else as.double(TREND),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("simss", y = if (is.double(y)) y else as.double(y),
     state = if (is.double(state)) state else as.double(state),
     as.integer(m), as.integer(n), as.integer(p), as.integer(sampleT),
     if (is.double(input)) input else as.double(input), if (is.double(w)) w else as.double(w),
     if (is.double(e)) e else as.double(e), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(is.innov.SS(model)),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("smooth", state = array(as.double(filter$state), dim(filter$state)),
     track = array(as.double(filter$track), dim(filter$track)),
     u, if (is.double(outputData(data))) outputData(data) else as.double(outputData(data)),
     as.integer(n), as.integer(m), as.integer(p), sampleT = as.integer(sampleT),
     as.double(model$F), as.double(G), as.double(model$H), as.double(RR),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), double(IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
    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: 2013.3-2
Check: R code for possible problems
Result: NOTE
    forecastCovEstimatorsWRTtrue: no visible global function definition for
     ‘setRNG’
    forecastCovReductionsWRTtrue: no visible global function definition for
     ‘setRNG’
    forecastCovWRTtrue: no visible global function definition for ‘setRNG’
    makeTSnoise: no visible global function definition for ‘setRNG’
    simulate.SS: no visible global function definition for ‘setRNG’
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-x86

Version: 2013.3-2
Check: Rd line widths
Result: NOTE
    Rd file 'forecastCov.Rd':
     \usage lines wider than 90 characters:
     zero=FALSE, trend=FALSE, estimation.sample= Tobs(data), compiled=.DSEflags()$COMPILED)
    
    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

Version: 2013.3-2
Check: foreign function calls
Result: NOTE
    Calls with DUP != TRUE:
     .Fortran("datepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), as.integer(p), predictT = as.integer(TT),
     err, DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(model$A)[1]),
     as.integer(dim(model$B)[1]), as.integer(dim(C)[1]), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$A, model$B, C, TREND, as.integer(is), matrix(double(1),
     is, is), matrix(double(1), is, is), double(is), integer(is *
     is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(n), as.integer(p), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$F, G, model$H, K, Q, R, as.integer(gain), z, P, as.integer(IS),
     matrix(double(1), IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), n, n), matrix(double(1), p,
     p), rep(double(1), IS), rep(double(1), IS), rep(double(1),
     IS), integer(IS * IS), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(obj$A)[1]),
     as.integer(dim(obj$B)[1]), as.integer(dim(C)[1]), as.integer(TT),
     u, outputData(data), obj$A, obj$B, C, TREND, as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = matrix(double(1), TT,
     p), as.integer(m), as.integer(n), as.integer(p), as.integer(TT),
     u, outputData(data), obj$F, G, obj$H, K, Q, R, as.integer(gain),
     z, P, as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("arma", pred = matrix(1e+20, predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(m), as.integer(p), as.integer(dim(A)[1]), as.integer(dim(B)[1]),
     as.integer(dim(C)[1]), sampleT = as.integer(sampleT), predictT = as.integer(predictT),
     as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(A)) A else as.double(A),
     if (is.double(B)) B else as.double(B), if (is.double(C)) C else as.double(C),
     if (is.double(TREND)) TREND else as.double(TREND), as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kf", pred = matrix(double(1), predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(return.state), state = state, as.integer(return.track &
     !Innov), track = if (is.double(track)) track else as.double(track),
     as.integer(m), as.integer(n), as.integer(p), sampleT = as.integer(sampleT),
     predictT = as.integer(predictT), as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(Innov),
     if (is.double(z)) z else as.double(z), if (is.double(P)) P else as.double(P),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("simrma", y = if (is.double(y)) y else as.double(y),
     if (is.double(y0)) y0 else as.double(y0), as.integer(m),
     as.integer(p), as.integer(a), as.integer(b), as.integer(cc),
     as.integer(sampleT), as.double(input[1:sampleT, ]), if (is.double(input0)) input0 else as.double(input0),
     if (is.double(noise$w)) noise$w else as.double(noise$w),
     if (is.double(noise$w0)) noise$w0 else as.double(noise$w0),
     if (is.double(A)) A else as.double(A), if (is.double(B)) B else as.double(B),
     if (is.double(C)) C else as.double(C), if (is.double(TREND)) TREND else as.double(TREND),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("simss", y = if (is.double(y)) y else as.double(y),
     state = if (is.double(state)) state else as.double(state),
     as.integer(m), as.integer(n), as.integer(p), as.integer(sampleT),
     if (is.double(input)) input else as.double(input), if (is.double(w)) w else as.double(w),
     if (is.double(e)) e else as.double(e), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(is.innov.SS(model)),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("smooth", state = array(as.double(filter$state), dim(filter$state)),
     track = array(as.double(filter$track), dim(filter$track)),
     u, if (is.double(outputData(data))) outputData(data) else as.double(outputData(data)),
     as.integer(n), as.integer(m), as.integer(p), sampleT = as.integer(sampleT),
     as.double(model$F), as.double(G), as.double(model$H), as.double(RR),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), double(IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
    DUP = FALSE is deprecated and will be disabled in future versions of R.
Flavors: r-patched-linux-x86_64, r-patched-solaris-x86

Version: 2013.3-2
Flags: --no-tests
Check: dependencies in R code
Result: NOTE
    'library' or 'require' call to ‘setRNG’ which was already attached by Depends.
     Please remove these calls from your code.
    Package in Depends field not imported from: ‘setRNG’
     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.
Flavor: r-patched-solaris-sparc

Version: 2013.3-2
Flags: --no-tests
Check: foreign function calls
Result: NOTE
    Calls with DUP != TRUE:
     .Fortran("datepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), as.integer(p), predictT = as.integer(TT),
     err, DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(model$A)[1]),
     as.integer(dim(model$B)[1]), as.integer(dim(C)[1]), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$A, model$B, C, TREND, as.integer(is), matrix(double(1),
     is, is), matrix(double(1), is, is), double(is), integer(is *
     is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfepr", forecastCov = cov, as.integer(discard.before),
     as.integer(horizons), as.integer(length(horizons)), sample.size = as.integer(rep(0,
     length(horizons))), pred = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(n), as.integer(p), predictT = as.integer(TT),
     as.integer(nrow(outputData(data))), u, outputData(data),
     model$F, G, model$H, K, Q, R, as.integer(gain), z, P, as.integer(IS),
     matrix(double(1), IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), n, n), matrix(double(1), p,
     p), rep(double(1), IS), rep(double(1), IS), rep(double(1),
     IS), integer(IS * IS), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("rmaprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = array(double(1), dim(outputData(data))),
     as.integer(m), as.integer(p), as.integer(dim(obj$A)[1]),
     as.integer(dim(obj$B)[1]), as.integer(dim(C)[1]), as.integer(TT),
     u, outputData(data), obj$A, obj$B, C, TREND, as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kfprj", proj = proj, as.integer(discard.before), as.integer(horizons),
     as.integer(length(horizons)), ey = matrix(double(1), TT,
     p), as.integer(m), as.integer(n), as.integer(p), as.integer(TT),
     u, outputData(data), obj$F, G, obj$H, K, Q, R, as.integer(gain),
     z, P, as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("arma", pred = matrix(1e+20, predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(m), as.integer(p), as.integer(dim(A)[1]), as.integer(dim(B)[1]),
     as.integer(dim(C)[1]), sampleT = as.integer(sampleT), predictT = as.integer(predictT),
     as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(A)) A else as.double(A),
     if (is.double(B)) B else as.double(B), if (is.double(C)) C else as.double(C),
     if (is.double(TREND)) TREND else as.double(TREND), as.integer(is),
     matrix(double(1), is, is), matrix(double(1), is, is), double(is),
     integer(is * is), DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("kf", pred = matrix(double(1), predictT, p), as.integer(length(error.weights)),
     weighted.sqerror = matrix(0, sampleT, p), error.weights = if (is.double(error.weights)) error.weights else as.double(error.weights),
     as.integer(return.state), state = state, as.integer(return.track &
     !Innov), track = if (is.double(track)) track else as.double(track),
     as.integer(m), as.integer(n), as.integer(p), sampleT = as.integer(sampleT),
     predictT = as.integer(predictT), as.integer(Tobs(y)), if (is.double(u)) u else as.double(u),
     if (is.double(y)) y else as.double(y), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(Innov),
     if (is.double(z)) z else as.double(z), if (is.double(P)) P else as.double(P),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     n, n), matrix(double(1), p, p), rep(double(1), IS), rep(double(1),
     IS), rep(double(1), IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
     .Fortran("simrma", y = if (is.double(y)) y else as.double(y),
     if (is.double(y0)) y0 else as.double(y0), as.integer(m),
     as.integer(p), as.integer(a), as.integer(b), as.integer(cc),
     as.integer(sampleT), as.double(input[1:sampleT, ]), if (is.double(input0)) input0 else as.double(input0),
     if (is.double(noise$w)) noise$w else as.double(noise$w),
     if (is.double(noise$w0)) noise$w0 else as.double(noise$w0),
     if (is.double(A)) A else as.double(A), if (is.double(B)) B else as.double(B),
     if (is.double(C)) C else as.double(C), if (is.double(TREND)) TREND else as.double(TREND),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("simss", y = if (is.double(y)) y else as.double(y),
     state = if (is.double(state)) state else as.double(state),
     as.integer(m), as.integer(n), as.integer(p), as.integer(sampleT),
     if (is.double(input)) input else as.double(input), if (is.double(w)) w else as.double(w),
     if (is.double(e)) e else as.double(e), if (is.double(FF)) FF else as.double(FF),
     if (is.double(G)) G else as.double(G), if (is.double(H)) H else as.double(H),
     if (is.double(K)) K else as.double(K), if (is.double(Q)) Q else as.double(Q),
     if (is.double(R)) R else as.double(R), as.integer(is.innov.SS(model)),
     DUP = .DSEflags()$DUP, PACKAGE = "dse")
     .Fortran("smooth", state = array(as.double(filter$state), dim(filter$state)),
     track = array(as.double(filter$track), dim(filter$track)),
     u, if (is.double(outputData(data))) outputData(data) else as.double(outputData(data)),
     as.integer(n), as.integer(m), as.integer(p), sampleT = as.integer(sampleT),
     as.double(model$F), as.double(G), as.double(model$H), as.double(RR),
     as.integer(IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), matrix(double(1), IS, IS), matrix(double(1),
     IS, IS), double(IS), integer(IS * IS), DUP = .DSEflags()$DUP,
     PACKAGE = "dse")
    DUP = FALSE is deprecated and will be disabled in future versions of R.
Flavor: r-patched-solaris-sparc

Version: 2013.3-2
Flags: --no-tests
Check: R code for possible problems
Result: NOTE
    forecastCovEstimatorsWRTtrue: no visible global function definition for
     ‘setRNG’
    forecastCovReductionsWRTtrue: no visible global function definition for
     ‘setRNG’
    forecastCovWRTtrue: no visible global function definition for ‘setRNG’
    makeTSnoise: no visible global function definition for ‘setRNG’
    simulate.SS: no visible global function definition for ‘setRNG’
Flavor: r-patched-solaris-sparc

Version: 2013.3-2
Check: dependencies in R code
Result: NOTE
    ‘library’ or ‘require’ call to ‘setRNG’ which was already attached by Depends.
     Please remove these calls from your code.
    Package in Depends field not imported from: ‘setRNG’
     These packages need to be imported from for the case 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.
Flavor: r-release-osx-x86_64-snowleopard