Description Objects Slots Methods Author(s) References See Also Examples
S4 class for storing results of the robust rank correlation test
Objects of this class can be created by calling rococo.test
.
The following slots are defined for RococoTestResults
objects:
count
:number of times in which the test
statistic for a random shuffle exceeded the test statistic of the
true data; see rococo.test
.
tnorm
:list identifying t-norm to use or
two-argument function; see rococo
.
If one of the standard choices "min"
, "prod"
, or
"lukasiewicz"
has been used, the list has one component,
name
that contains the string identifying the t-norm.
If a user-defined function has been used, the list has two
components: name
contains "user-defined t-norm"
or the name
attribute of the function object if available
and def
contains the function object itself.
input
:character string describing the input for which
rococo.test
has been called.
length
:number of samples for which
rococo.test
has been called.
p.value
:p-value of test.
p.value.approx
:p-value as based on a normal approximation of the null distribution.
r.values
:vector containing tolerance levels for the
two inputs; see rococo.test
or
rococo
.
numtests
:number of (random) shuffles performed by
rococo.test
.
exact
:logical indicating whether p-value has been
computed exactly; see rococo.test
.
similarity
:character (vector) identifying the
similarity measure(s) used by rococo.test
.
sample.gamma
:test statistic (robust gamma rank
correlation coefficient) determined by
rococo.test
.
H0gamma.mu
:empirical mean of test statistic for random shuffles
H0gamma.sd
:empirical standard deviation of test statistic for random shuffles
perm.gamma
:in case rococo.test
was
called with storeValues=TRUE
, this slot contains the
vector of test statistics for random shuffles.
alternative
:alternative hypothesis used by
rococo.test
.
signature(object = "RococoTestResults")
: d
displays the most important information stored in
object
Martin Krone & Ulrich Bodenhofer rococo@bioinf.jku.at
http://www.bioinf.jku.at/software/rococo/
U. Bodenhofer, M. Krone, and F. Klawonn (2013). Testing noisy numerical data for monotonic association. Inform. Sci. 245:21-37. DOI: 10.1016/j.ins.2012.11.026.
U. Bodenhofer and F. Klawonn (2008). Robust rank correlation coefficients on the basis of fuzzy orderings: initial steps. Mathware Soft Comput. 15(1):5-20.
rococo.test
, rococo
,
show-methods
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ## create data
f <- function(x) ifelse(x > 0.9, x - 0.9, ifelse(x < -0.9, x + 0.9, 0))
x <- rnorm(25)
y <- f(x) + rnorm(25, sd=0.1)
## perform correlation tests
ret <- rococo.test(x, y, similarity="classical", alternative="greater")
show(ret)
ret <- rococo.test(x, y, similarity="linear", alternative="greater")
show(ret)
ret <- rococo.test(x, y, similarity=c("classical", "gauss"),
r=c(0, 0.1), alternative="greater",
numtests=10000)
show(ret)
|
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