# PermutationDistribution-methods

##### Computation of the Permutation Distribution

Methods for computation of the density function, distribution function, quantile function, random numbers and support of the permutation distribution.

- Keywords
- methods, distribution, htest

##### Usage

```
# S4 method for NullDistribution
dperm(object, x, …)
# S4 method for IndependenceTest
dperm(object, x, …)
```# S4 method for NullDistribution
pperm(object, q, …)
# S4 method for IndependenceTest
pperm(object, q, …)

# S4 method for NullDistribution
qperm(object, p, …)
# S4 method for IndependenceTest
qperm(object, p, …)

# S4 method for NullDistribution
rperm(object, n, …)
# S4 method for IndependenceTest
rperm(object, n, …)

# S4 method for NullDistribution
support(object, …)
# S4 method for IndependenceTest
support(object, …)

##### Arguments

- object
an object from which the density function, distribution function, quantile function, random numbers or support of the permutation distribution can be computed.

- x, q
a numeric vector, the quantiles for which the density function or distribution function is computed.

- p
a numeric vector, the probabilities for which the quantile function is computed.

- n
a numeric vector, the number of observations. If

`length(n) > 1`

, the length is taken to be the number required.- …
further arguments to be passed to methods.

##### Details

The methods `dperm`

, `pperm`

, `qperm`

, `rperm`

and
`support`

compute the density function, distribution function, quantile
function, random deviates and support, respectively, of the permutation
distribution.

##### Value

The density function, distribution function, quantile function, random
deviates or support of the permutation distribution computed from
`object`

. A numeric vector.

##### Note

The density of asymptotic permutation distributions for maximum-type tests or
exact permutation distributions obtained by the split-up algoritm is reported
as `NA`

. The quantile function of asymptotic permutation distributions
for maximum-type tests cannot be computed for `p`

less than 0.5, due to
limitations in the mvtnorm package. The support of exact permutation
distributions obtained by the split-up algorithm is reported as `NA`

.

In versions of coin prior to 1.1-0, the support of asymptotic
permutation distributions was given as an interval containing 99.999 % of the
probability mass. It is now reported as `NA`

.

##### Examples

```
# NOT RUN {
## Two-sample problem
dta <- data.frame(
y = rnorm(20),
x = gl(2, 10)
)
## Exact Ansari-Bradley test
at <- ansari_test(y ~ x, data = dta, distribution = "exact")
## Support of the exact distribution of the Ansari-Bradley statistic
supp <- support(at)
## Density of the exact distribution of the Ansari-Bradley statistic
dens <- dperm(at, x = supp)
## Plotting the density
plot(supp, dens, type = "s")
## 95% quantile
qperm(at, p = 0.95)
## One-sided p-value
pperm(at, q = statistic(at))
## Random number generation
rperm(at, n = 5)
# }
```

*Documentation reproduced from package coin, version 1.3-1, License: GPL-2*