# PermutationDistribution-methods: Computation of the Permutation Distribution In coin: Conditional Inference Procedures in a Permutation Test Framework

## Description

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

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```## S4 method for signature 'NullDistribution' dperm(object, x, ...) ## S4 method for signature 'IndependenceTest' dperm(object, x, ...) ## S4 method for signature 'NullDistribution' pperm(object, q, ...) ## S4 method for signature 'IndependenceTest' pperm(object, q, ...) ## S4 method for signature 'NullDistribution' qperm(object, p, ...) ## S4 method for signature 'IndependenceTest' qperm(object, p, ...) ## S4 method for signature 'NullDistribution' rperm(object, n, ...) ## S4 method for signature 'IndependenceTest' rperm(object, n, ...) ## S4 method for signature 'NullDistribution' support(object, ...) ## S4 method for signature '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

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26``` ```## 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) ```

### Example output ```Loading required package: survival
 1.669331
 0.9239483
 -0.6070295  1.0623017  0.7587869  0.3035148 -0.6070295
```

coin documentation built on Oct. 8, 2021, 9:07 a.m.