Mutoss (multiple hypotheses testing in an open software system) aims at providing a unified, extensible interface covering a large spectrum of multiple hypotheses testing procedures in R. Features a GUI and a simulation tool. Funded by PASCAL2.
checking dependencies in R code ... NOTE
‘library’ or ‘require’ calls to packages already attached by Depends:
‘multcomp’ ‘multtest’ ‘plotrix’
Please remove these calls from your code.
See the information on DESCRIPTION files in the chapter ‘Creating R
packages’ of the ‘Writing R Extensions’ manual.
* checking sizes of PDF files under ‘inst/doc’ ... NOTE
‘qpdf’ made some significant size reductions:
compacted ‘simToolManual.pdf’ from 438Kb to 217Kb
compacted ‘simToolVignette.pdf’ from 425Kb to 208Kb
consider running tools::compactPDF() on these files
`* checking Rd line widths ... NOTE
Rd file ‘compareMutoss.Rd’:
\examples lines wider than 100 characters:
mu.test.obj.1 <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=bonferroni, label="Bonferroni Correction", alpha=0.05, silent=T ... [TRUNCATED]
mu.test.obj.2 <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=holm, label="Holm‘s step-down-procedure", alpha=0.05, silent=T) ... [TRUNCATED]
mu.test.obj.3 <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=aorc, label="Asymtotically optimal rejection curve", alpha=0.05 ... [TRUNCATED]
Rd file ’gatherParameters.Rd‘:
\examples lines wider than 100 characters:
myGen <- function(n, n0) list(procInput=list(pValues = c(runif(n-n0, 0, 0.01), runif(n0))), groundTruth = c(rep(FALSE, times=n-n0), rep ... [TRUNCATED]
list(list(funName="BH", fun=function(pValues, alpha) BH(pValues, alpha, silent=TRUE), alpha=c(0.25, 0.5)),
Rd file ’gatherStatistics.Rd‘:
\examples lines wider than 100 characters:
myGen <- function(n, n0) list(procInput=list(pValues = c(runif(n-n0, 0, 0.01), runif(n0))), groundTruth = c(rep(FALSE, times=n-n0), rep ... [TRUNCATED]
list(list(funName="BH", fun=function(pValues, alpha) BH(pValues, alpha, silent=TRUE), alpha=c(0.25, 0.5)),
result2 <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error), list(q05 = function(x) quantile(x, probs=0.05), MEAN = mean, ... [TRUNCATED]
Rd file ’multcomp.wrapper.Rd‘:
\examples lines wider than 100 characters:
multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), hypotheses = "Tukey", alternative="two.sided", factorC="tension",alpha=0.05)
multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), hypotheses= "Williams", alternative="two.sided",alpha=0.05,factorC="tension" ... [TRUNCATED]
multcomp.wrapper(aov(breaks ~ tension, data = warpbreaks), hypotheses=K, alternative="two.sided",alpha=0.05,factorC="tension")
multcomp.wrapper(aov(breaks ~ tension_wool, data = warpbreaks), hypotheses="Tukey", alternative="two.sided",alpha=0.05,factorC="wool")
multcomp.wrapper(aov(breaks ~ tension_wool, data = warpbreaks), hypotheses="Tukey", alternative="two.sided",alpha=0.05,factorC="tension ... [TRUNCATED]
multcomp.wrapper(aov(breaks ~ tension*wool, data = warpbreaks), hypotheses=K, alternative="two.sided",alpha=0.05, factorC="tension")
multcomp.wrapper(model=lm(Sepal.Length ~ Species, data=iris),hypotheses="Tukey","two.sided",alpha=0.05, factorC="Species")
multcomp.wrapper(model=lm(Sepal.Length ~ Species, data=iris),hypotheses=K,"two.sided",alpha=0.05, factorC="Species")
Rd file ’mutoss.apply.Rd‘:
\examples lines wider than 100 characters:
newObjectBonf <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=bonferroni, label="Bonferroni Correction", alpha=0.05)
newObjectHolm <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=holm, label="Holm’s step-down-procedure", alpha=0.05, silent=T)
newObjectAORC <- mutoss.apply(new(Class="Mutoss", pValues=runif(10)), f=aorc, label="Asymptotically optimal rejection curve", alpha=0.0 ... [TRUNCATED]
Rd file ‘simulation.Rd’:
\examples lines wider than 100 characters:
myGen <- function(n, n0) list(procInput=list(pValues = c(runif(n-n0, 0, 0.01), runif(n0))), groundTruth = c(rep(FALSE, times=n-n0), rep ... [TRUNCATED]
list(list(funName="BH", fun=function(pValues, alpha) BH(pValues, alpha, silent=TRUE), alpha=c(0.25, 0.5)),
result <- gatherStatistics(sim, list(NumOfType1Err = NumberOfType1Error), list(median=median, mean=mean, sd=sd))
`
* checking examples ... OK
Examples with CPU or elapsed time > 5s
user system elapsed
aorc 6.016 0.752 6.906
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