CRAN Package Check Results for Package hhsmm

Last updated on 2021-06-14 15:50:10 CEST.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 0.1 14.32 70.79 85.11 OK
r-devel-linux-x86_64-debian-gcc 0.1 11.83 55.90 67.73 OK
r-devel-linux-x86_64-fedora-clang 0.1 111.38 NOTE
r-devel-linux-x86_64-fedora-gcc 0.1 96.46 NOTE
r-devel-windows-x86_64 0.1 20.00 85.00 105.00 NOTE
r-devel-windows-x86_64-gcc10-UCRT 0.1 NOTE
r-patched-linux-x86_64 0.1 12.55 65.87 78.42 OK
r-patched-solaris-x86 0.1 173.20 NOTE
r-release-linux-x86_64 0.1 13.31 64.48 77.79 OK
r-release-macos-arm64 0.1 ERROR
r-release-macos-x86_64 0.1 NOTE
r-release-windows-ix86+x86_64 0.1 24.00 119.00 143.00 NOTE
r-oldrel-macos-x86_64 0.1 NOTE
r-oldrel-windows-ix86+x86_64 0.1 20.00 115.00 135.00 NOTE

Additional issues

M1mac noLD valgrind

Check Details

Version: 0.1
Check: installed package size
Result: NOTE
     installed size is 5.5Mb
     sub-directories of 1Mb or more:
     data 5.2Mb
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-windows-x86_64, r-patched-solaris-x86, r-release-macos-arm64, r-release-macos-x86_64, r-release-windows-ix86+x86_64, r-oldrel-macos-x86_64, r-oldrel-windows-ix86+x86_64

Version: 0.1
Check: dependencies in R code
Result: NOTE
    Namespaces in Imports field not imported from:
     ‘Rcpp’ ‘Rdpack’
     All declared Imports should be used.
Flavors: r-devel-linux-x86_64-fedora-clang, r-devel-linux-x86_64-fedora-gcc, r-devel-windows-x86_64-gcc10-UCRT, r-patched-solaris-x86, r-release-macos-arm64, r-release-macos-x86_64, r-oldrel-macos-x86_64

Version: 0.1
Check: examples
Result: ERROR
    Running examples in ‘hhsmm-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: make_model
    > ### Title: make a hhsmmspec model
    > ### Aliases: make_model
    >
    > ### ** Examples
    >
    > J <- 3
    > initial <- c(1,0,0)
    > semi <- c(FALSE,TRUE,FALSE)
    > P <- matrix(c(0.8, 0.1, 0.1, 0.5, 0, 0.5, 0.1, 0.2, 0.7), nrow = J, byrow=TRUE)
    > par <- list(mu = list(list(7,8),list(10,9,11),list(12,14)),
    + sigma = list(list(3.8,4.9),list(4.3,4.2,5.4),list(4.5,6.1)),
    + mix.p = list(c(0.3,0.7),c(0.2,0.3,0.5),c(0.5,0.5)))
    > sojourn <- list(shape = c(0,3,0), scale = c(0,10,0), type = "gamma")
    > model <- hhsmmspec(init = initial, transition = P, parms.emis = par,
    + dens.emis = dmixmvnorm, sojourn = sojourn, semi = semi)
    > train <- simulate(model, nsim = c(10,8,8,18), seed = 1234, remission = rmixmvnorm)
    > clus = initial_cluster(train,nstate=3,nmix=c(2,2,2),ltr=FALSE,
    + final.absorb=FALSE,verbose=TRUE)
    Within sequence clustering ...
    State 1
    Between sequence clustering ...
    State 2
    Between sequence clustering ...
    State 3
    Between sequence clustering ...
    > par = initial_estimate(clus,verbose=TRUE)
    Intitial estimation ....
    State 1 estimation
    
    [.. ] 25%
    [..... ] 50%
    [....... ] 75%
    [..........] 100%
    Mixture component 1 estimation
    Mixture component 2 estimation
    State 2 estimation
    
    [.. ] 25%
    [..... ] 50%
    [....... ] 75%
    [..........] 100%
    Mixture component 1 estimation
    Mixture component 2 estimation
    State 3 estimation
    
    [.. ] 25%
    [..... ] 50%
    [....... ] 75%
    [..........] 100%
    Mixture component 1 estimation
    Mixture component 2 estimation
    > model = make_model(par,semi=NULL,M=max(train$N),sojourn="auto")
    Warning in chisq.test(x = observed, p = expected.gamma) :
     Chi-squared approximation may be incorrect
    Warning in chisq.test(x = observed, p = expected.lnorm) :
     Chi-squared approximation may be incorrect
    Warning in chisq.test(x = observed, p = expected.poisson) :
     Chi-squared approximation may be incorrect
    Warning in chisq.test(x = observed, p = expected.weibull) :
     Chi-squared approximation may be incorrect
    Warning in chisq.test(x = observed, p = expected.nbinom) :
     Chi-squared approximation may be incorrect
    Warning in chisq.test(x = observed, p = expected.log) :
     Chi-squared approximation may be incorrect
    Warning in min(which(d0jc >= 0.1 * t)) :
     no non-missing arguments to min; returning Inf
    Error in breaks[l]:(breaks[l + 1] - 1) :
     result would be too long a vector
    Calls: make_model
    Execution halted
Flavor: r-release-macos-arm64