permutationTest.object.Rd
This class of objects is returned by functions that perform permutation tests.
Objects of class "permutationTest"
are lists that contain information about
the null and alternative hypotheses, the estimated distribution parameters, the
test statistic and the p-value. They also contain the permutation distribution
of the statistic (or a sample of the permutation distribution).
Objects of S3 class "permutationTest"
are returned by any of the
EnvStats functions that perform permutation tests. Currently, these are:
oneSamplePermutationTest
, twoSamplePermutationTestLocation
, and
twoSamplePermutationTestProportion
.
Generic functions that have methods for objects of class
"permutationTest"
include: print
, plot
.
A legitimate list of class "permutationTest"
includes the components
listed in the help file for htest.object
. In addition, the following
components must be included in a legitimate list of class "permutationTest"
:
Required Components
The following components must be included in a legitimate list of
class "permutationTest"
.
numeric vector containing values of the statistic for the permutation distribution.
When exact=FALSE
, the vector is comprised of values sampled from the full
permutation distribution.
logical scalar indicating whether the exact permutation distribution was used for
the test (exact=TRUE
), or if instead the permutation distribution was
sampled (exact=FALSE
).
Optional Components
The following component may optionally be included in an object of
of class "permutationTest"
:
integer or vector of integers indicating the seed that was used for sampling the
permutation distribution. This component is present only if exact=FALSE
.
numeric vector containing the probabilities associated with each element of
the component stat.dist
. This component is only returned by the
function twoSamplePermutationTestProportion
.
Since objects of class "permutationTest"
are lists, you may extract
their components with the $
and [[
operators.
# Create an object of class "permutationTest", then print it and plot it.
#------------------------------------------------------------------------
set.seed(23)
dat <- rlogis(10, location = 7, scale = 2)
permutationTest.obj <- oneSamplePermutationTest(dat, mu = 5,
alternative = "greater", exact = TRUE)
mode(permutationTest.obj)
#> [1] "list"
#[1] "list"
class(permutationTest.obj)
#> [1] "permutationTest"
#[1] "permutationTest"
names(permutationTest.obj)
#> [1] "statistic" "parameters" "p.value"
#> [4] "estimate" "null.value" "alternative"
#> [7] "method" "estimation.method" "sample.size"
#> [10] "data.name" "bad.obs" "stat.dist"
#> [13] "exact"
# [1] "statistic" "parameters" "p.value"
# [4] "estimate" "null.value" "alternative"
# [7] "method" "estimation.method" "sample.size"
#[10] "data.name" "bad.obs" "stat.dist"
#[13] "exact"
#==========
# Print the results of the test
#------------------------------
permutationTest.obj
#>
#> Results of Hypothesis Test
#> --------------------------
#>
#> Null Hypothesis: Mean (Median) = 5
#>
#> Alternative Hypothesis: True Mean (Median) is greater than 5
#>
#> Test Name: One-Sample Permutation Test
#> (Exact)
#>
#> Estimated Parameter(s): Mean = 9.977294
#>
#> Data: dat
#>
#> Sample Size: 10
#>
#> Test Statistic: Sum(x - 5) = 49.77294
#>
#> P-value: 0.001953125
#>
#Results of Hypothesis Test
#--------------------------
#
#Null Hypothesis: Mean (Median) = 5
#
#Alternative Hypothesis: True Mean (Median) is greater than 5
#
#Test Name: One-Sample Permutation Test
# (Exact)
#
#Estimated Parameter(s): Mean = 9.977294
#
#Data: dat
#
#Sample Size: 10
#
#Test Statistic: Sum(x - 5) = 49.77294
#
#P-value: 0.001953125
#==========
# Plot the results of the test
#-----------------------------
dev.new()
plot(permutationTest.obj)
#==========
# Extract the test statistic
#---------------------------
permutationTest.obj$statistic
#> Sum(x - 5)
#> 49.77294
#Sum(x - 5)
# 49.77294
#==========
# Clean up
#---------
rm(permutationTest.obj)
graphics.off()