# TailAnova: Heavy-tail ANOVA In flood: Statistical Methods for the (Regional) Analysis of Flood Frequency

## Description

A test of heavy-tail homogeneity, that is, equality of the positive extreme value index for all d columns of `x`.

## Usage

 `1` ```TailAnova(x, k, k.qu = 20, type = "evopt", cf = TRUE) ```

## Arguments

 `x` Matrix of observations `k` Number of relative excesses involved in the estimation of the extreme value index gamma. If `k` is missing, it will be set to k=floor(2*n^(2/3)/d^(1/3)), where d is the number of columns of the matrix `x` and n the length of each column after removing missing values. `k.qu` Tuning parameter for estimation of empirical variance; only needed if `type="opt"`. `type` Choose either `"evopt"` if extreme value dependent, `"ind"` if independent or `"opt"` for arbitrarily dependent components. `cf` If `TRUE`, a correctur factor is used, which improves the size at the cost of power.

## Value

Test statistic and p-value.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11``` ```library("evd") set.seed(6754) x1 <- rgev(150, loc = 2, scale = 1, shape=0.4) x2 <- rgev(150, loc = 2.5, scale = 1, shape=0.1) # H_0 violated because of different shapes x <- cbind(x1, x2) TailAnova(x) x1 <- rgev(150, loc = 2, scale = 1, shape=0.3) x2 <- rgev(150, loc = 2.5, scale = 1, shape=0.3) # H_0 not violated because of same shapes x <- cbind(x1, x2) TailAnova(x) ```

flood documentation built on May 30, 2017, 8:25 a.m.