CRAN Package Check Results for Package glmnet

Last updated on 2016-08-30 12:46:58.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 2.0-5 19.42 63.82 83.24 OK
r-devel-linux-x86_64-debian-gcc 2.0-5 19.08 63.26 82.33 OK
r-devel-linux-x86_64-fedora-clang 2.0-5 155.97 OK
r-devel-linux-x86_64-fedora-gcc 2.0-5 146.35 OK
r-devel-osx-x86_64-clang 2.0-5 123.41 OK
r-devel-windows-ix86+x86_64 2.0-5 56.00 127.00 183.00 OK
r-patched-linux-x86_64 2.0-5 18.67 64.88 83.55 OK
r-patched-solaris-sparc 2.0-5 1196.80 OK
r-patched-solaris-x86 2.0-5 165.20 ERROR
r-release-linux-x86_64 2.0-5 18.36 61.14 79.50 OK
r-release-osx-x86_64-mavericks 2.0-5 OK
r-release-windows-ix86+x86_64 2.0-5 47.00 116.00 163.00 OK
r-oldrel-windows-ix86+x86_64 2.0-5 48.00 169.00 217.00 OK

Check Details

Version: 2.0-5
Check: examples
Result: ERROR
    Running examples in ‘glmnet-Ex.R’ failed
    The error most likely occurred in:
    
    > ### Name: cv.glmnet
    > ### Title: Cross-validation for glmnet
    > ### Aliases: cv.glmnet
    > ### Keywords: models regression
    >
    > ### ** Examples
    >
    > set.seed(1010)
    > n=1000;p=100
    > nzc=trunc(p/10)
    > x=matrix(rnorm(n*p),n,p)
    > beta=rnorm(nzc)
    > fx= x[,seq(nzc)] %*% beta
    > eps=rnorm(n)*5
    > y=drop(fx+eps)
    > px=exp(fx)
    > px=px/(1+px)
    > ly=rbinom(n=length(px),prob=px,size=1)
    > set.seed(1011)
    > cvob1=cv.glmnet(x,y)
    > plot(cvob1)
    > coef(cvob1)
    101 x 1 sparse Matrix of class "dgCMatrix"
     1
    (Intercept) -0.114499004
    V1 -0.249682465
    V2 0.354656099
    V3 .
    V4 -0.250595374
    V5 -0.220882137
    V6 0.281975536
    V7 0.226455138
    V8 -1.389842399
    V9 1.055440917
    V10 0.185144685
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    V75 -0.177175572
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    > predict(cvob1,newx=x[1:5,], s="lambda.min")
     1
    [1,] -1.3447658
    [2,] 0.9443441
    [3,] 0.6989746
    [4,] 1.8698290
    [5,] -4.7372693
    > title("Gaussian Family",line=2.5)
    > set.seed(1011)
    > cvob1a=cv.glmnet(x,y,type.measure="mae")
    > plot(cvob1a)
    > title("Gaussian Family",line=2.5)
    > set.seed(1011)
    > par(mfrow=c(2,2),mar=c(4.5,4.5,4,1))
    > cvob2=cv.glmnet(x,ly,family="binomial")
    > plot(cvob2)
    > title("Binomial Family",line=2.5)
    > frame()
    > set.seed(1011)
    > cvob3=cv.glmnet(x,ly,family="binomial",type.measure="class")
    > plot(cvob3)
    > title("Binomial Family",line=2.5)
    > set.seed(1011)
    > cvob3a=cv.glmnet(x,ly,family="binomial",type.measure="auc")
    > plot(cvob3a)
    > title("Binomial Family",line=2.5)
    > set.seed(1011)
    > mu=exp(fx/10)
    > y=rpois(n,mu)
    > cvob4=cv.glmnet(x,y,family="poisson")
    > plot(cvob4)
    > title("Poisson Family",line=2.5)
    > # Multinomial
    > n=500;p=30
    > nzc=trunc(p/10)
    > x=matrix(rnorm(n*p),n,p)
    > beta3=matrix(rnorm(30),10,3)
    > beta3=rbind(beta3,matrix(0,p-10,3))
    > f3=x%*% beta3
    > p3=exp(f3)
    > p3=p3/apply(p3,1,sum)
    > g3=rmult(p3)
    > set.seed(10101)
    > cvfit=cv.glmnet(x,g3,family="multinomial")
    Error in apply(nz, 1, median) : dim(X) must have a positive length
    Calls: cv.glmnet -> apply
    Execution halted
Flavor: r-patched-solaris-x86