Last updated on 2015-03-04 03:46:55.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.2-6 | 0.82 | 76.67 | 77.50 | NOTE | |
| r-devel-linux-x86_64-debian-gcc | 1.2-6 | 0.80 | 75.71 | 76.52 | NOTE | |
| r-devel-linux-x86_64-fedora-clang | 1.2-6 | 160.49 | NOTE | |||
| r-devel-linux-x86_64-fedora-gcc | 1.2-6 | 156.85 | NOTE | |||
| r-devel-osx-x86_64-clang | 1.2-6 | 128.98 | OK | |||
| r-devel-windows-ix86+x86_64 | 1.2-6 | 3.00 | 109.00 | 112.00 | OK | |
| r-patched-linux-x86_64 | 1.2-6 | 0.88 | 78.58 | 79.46 | NOTE | |
| r-patched-solaris-sparc | 1.2-6 | 1335.00 | OK | |||
| r-patched-solaris-x86 | 1.2-6 | 177.60 | OK | |||
| r-release-linux-ix86 | 1.2-6 | 1.26 | 127.88 | 129.15 | NOTE | |
| r-release-linux-x86_64 | 1.2-6 | 0.90 | 78.00 | 78.90 | 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 | 8.00 | 129.00 | 137.00 | OK | |
| r-oldrel-windows-ix86+x86_64 | 1.2-6 | 4.00 | 114.00 | 118.00 | OK |
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-ix86, 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-ix86, 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