CRAN Package Check Results for Package plsgenomics

Last updated on 2014-12-19 08:48:37.

Flavor Version Tinstall Tcheck Ttotal Status Flags
r-devel-linux-x86_64-debian-clang 1.2-6 0.91 75.68 76.59 NOTE
r-devel-linux-x86_64-debian-gcc 1.2-6 0.86 74.77 75.62 NOTE
r-devel-linux-x86_64-fedora-clang 1.2-6 165.92 NOTE
r-devel-linux-x86_64-fedora-gcc 1.2-6 133.20 NOTE
r-devel-osx-x86_64-clang 1.2-6 132.26 OK
r-devel-windows-ix86+x86_64 1.2-6 4.00 111.00 115.00 OK
r-patched-linux-x86_64 1.2-6 1.13 77.85 78.98 NOTE
r-patched-solaris-sparc 1.2-6 1292.70 OK
r-patched-solaris-x86 1.2-6 177.40 OK
r-release-linux-ix86 1.2-6 1.25 106.08 107.34 OK
r-release-linux-x86_64 1.2-6 0.90 79.00 79.90 NOTE
r-release-osx-x86_64-mavericks 1.2-6 OK
r-release-osx-x86_64-snowleopard 1.2-6 WARN
r-release-windows-ix86+x86_64 1.2-6 4.00 115.00 119.00 OK
r-oldrel-windows-ix86+x86_64 1.2-6 4.00 121.00 125.00 OK

Check Details

Version: 1.2-6
Check: top-level files
Result: NOTE
    Non-standard files/directories found at top level:
     ‘copying’ ‘plsgenomics-Ex.R’
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: 1.2-6
Check: Rd line widths
Result: NOTE
    Rd file 'gsim.Rd':
     \examples lines wider than 100 characters:
     resP <- preprocess(Xtrain= Xtrain, Xtest=Xtest,Threshold = c(100,16000),Filtering=c(5,500),log10.scale=TRUE,row.stand=TRUE)
    
    Rd file 'gsim.cv.Rd':
     \examples lines wider than 100 characters:
     resP <- preprocess(Xtrain= Xtrain, Xtest=Xtest,Threshold = c(100,16000),Filtering=c(5,500),log10.scale=TRUE,row.stand=TRUE)
    
    Rd file 'mgsim.Rd':
     \examples lines wider than 100 characters:
     IndexLearn <- c(sample(which(SRBCT$Y==1),10),sample(which(SRBCT$Y==2),4),sample(which(SRBCT$Y==3),7),sample(which(SRBCT$Y==4),9))
     res <- mgsim(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],Lambda=0.001,h=19,Xtest=SRBCT$X[-IndexLearn,])
    
    Rd file 'mgsim.cv.Rd':
     \examples lines wider than 100 characters:
     IndexLearn <- c(sample(which(SRBCT$Y==1),10),sample(which(SRBCT$Y==2),4),sample(which(SRBCT$Y==3),7),sample(which(SRBCT$Y==4),9))
     hl <- mgsim.cv(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],LambdaRange=c(0.1),hRange=c(7,20))
     res <- mgsim(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],Lambda=hl$Lambda,h=hl$h,Xtest=SRBCT$X[-IndexLearn,])
    
    Rd file 'mrpls.Rd':
     \examples lines wider than 100 characters:
     IndexLearn <- c(sample(which(SRBCT$Y==1),10),sample(which(SRBCT$Y==2),4),sample(which(SRBCT$Y==3),7),sample(which(SRBCT$Y==4),9))
     res <- mrpls(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],Lambda=0.001,ncomp=2,Xtest=SRBCT$X[-IndexLearn,])
    
    Rd file 'mrpls.cv.Rd':
     \examples lines wider than 100 characters:
     IndexLearn <- c(sample(which(SRBCT$Y==1),10),sample(which(SRBCT$Y==2),4),sample(which(SRBCT$Y==3),7),sample(which(SRBCT$Y==4),9))
     nl <- mrpls.cv(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],LambdaRange=c(0.1,1),ncompMax=3)
     res <- mrpls(Ytrain=SRBCT$Y[IndexLearn],Xtrain=SRBCT$X[IndexLearn,],Lambda=nl$Lambda,ncomp=nl$ncomp,Xtest=SRBCT$X[-IndexLearn,])
    
    Rd file 'pls.lda.Rd':
     \examples lines wider than 100 characters:
     # Classify observations 1,2,3 (test set) using observations 4 to 38 (training set), with 2 PLS components
     pls.lda(Xtrain=leukemia$X[-(1:3),],Ytrain=leukemia$Y[-(1:3)],Xtest=leukemia$X[1:3,],ncomp=2,nruncv=0)
     # Classify observations 1,2,3 (test set) using observations 4 to 38 (training set), with the best number of components as determined by ... [TRUNCATED]
     pls.lda(Xtrain=leukemia$X[-(1:3),],Ytrain=leukemia$Y[-(1:3)],Xtest=leukemia$X[1:3,],ncomp=1:4,nruncv=20)
    
    Rd file 'pls.lda.cv.Rd':
     \examples lines wider than 100 characters:
     # Determine the best number of components to be used for classification using the cross-validation procedure
    
    Rd file 'pls.regression.Rd':
     \examples lines wider than 100 characters:
     pls.regression(Xtrain=Ecoli$CONNECdata,Ytrain=Ecoli$GEdata,Xtest=Ecoli$CONNECdata,ncomp=1:3,unit.weights=FALSE)
     pls.regression(Xtrain=Ecoli$CONNECdata,Ytrain=Ecoli$GEdata,Xtest=Ecoli$CONNECdata,ncomp=1:3,unit.weights=TRUE)
    
    Rd file 'preprocess.Rd':
     \usage lines wider than 90 characters:
     preprocess(Xtrain, Xtest=NULL,Threshold=c(100,16000),Filtering=c(5,500),log10.scale=TRUE,row.stand=TRUE)
     \examples lines wider than 100 characters:
     resP <- preprocess(Xtrain= Xtrain, Xtest=Xtest,Threshold = c(100,16000),Filtering=c(5,500),log10.scale=TRUE,row.stand=TRUE)
    
    Rd file 'rpls.Rd':
     \examples lines wider than 100 characters:
     res <- preprocess(Xtrain= Colon$X[IndexLearn,], Xtest=Colon$X[-IndexLearn,],Threshold = c(100,16000),Filtering=c(5,500),log10.scale=TRU ... [TRUNCATED]
    
    Rd file 'rpls.cv.Rd':
     \examples lines wider than 100 characters:
     res <- preprocess(Xtrain= Colon$X[IndexLearn,], Xtest=Colon$X[-IndexLearn,],Threshold = c(100,16000),Filtering=c(5,500),log10.scale=TRU ... [TRUNCATED]
     resrpls <- rpls(Ytrain=Colon$Y[IndexLearn],Xtrain=res$pXtrain,Lambda=nl$Lambda,ncomp=nl$ncomp,Xtest=res$pXtest)
    
    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: 1.2-6
Check: examples
Result: WARN
    checking a package with encoding 'latin1' in an ASCII locale
    
     OK
Flavor: r-release-osx-x86_64-snowleopard