View source: R/CompareObjects.R
compareMutoss | R Documentation |
Functions for comparing outputs of different procedures.
compareMutoss(...)
mu.compare.adjusted(comparison.list, identify.check=F)
mu.compare.critical(comparison.list, identify.check=F)
mu.compare.summary(comparison.list)
... |
An arbitrary number of Motoss class objects. |
comparison.list |
The output of the |
identify.check |
Logical parameter specifying if hypotheses should be identified on the output plots. |
These functions are used to compare the results of different multiple comparisons procedures stored as Mutoss class objects.
compareMutoss
takes as input an arbitrary number of Mutoss objects and arranges them in a simple list objects (non S4).
mu.compare.adjuted
, mu.compare.critical
and mu.compare.summary
take the output of the compareMutoss
and plots or summerize the results textually or graphically.
compareMutoss |
Returns a list with the following components: |
mu.compare.adjusted |
Creates a plot with the adjusted p-values for each procedure. |
mu.compare.critical |
Creates a plot with the critical values for each procedure and error rate. |
mu.compare.summary |
Creates a short textual summary for comparing results of different procedures. |
Jonathan Rosenblatt
# TODO: EXAMPLE PROBLEMS
## Not run:
\dontrun{Creating several Mutoss class objects}
mu.test.obj.1 <- mutoss.apply(new(Class="Mutoss",
pValues=runif(10)),
f=bonferroni,
label="Bonferroni Correction",
alpha=0.05,
silent=T)
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)
mu.test.obj.3 <- mutoss.apply(new(Class="Mutoss",
pValues=runif(10)),
f=aorc,
label="Asymtotically optimal rejection curve",
alpha=0.05,
startIDX_SUD = 1,
silent=T)
\dontrun{Trying to coercing a non-Mutoss object}
compareMutoss(1)
\dontrun{ Coercing several objects into a list}
compare.1<- compareMutoss(mu.test.obj.1, mu.test.obj.2)
compare.2<- compareMutoss(mu.test.obj.1, mu.test.obj.2, mu.test.obj.3)
\dontrun{Plotting the adjusted pvalues. Identification available.}
mu.compare.adjusted(compare.1, T)
mu.compare.adjusted(compare.2, T)
\dontrun{Plotting the critical values. Identification available.}
mu.compare.critical(compare.1, T)
mu.compare.critical(compare.2, T)
\dontrun{Showing a textual sumary}
mu.compare.summary(compare.1)
mu.compare.summary(compare.2)
## End(Not run)
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