maxblocks: Computes the normalized componentwise maxima with their...

In HiDimMaxStable: Inference on High Dimensional Max-Stable Distributions

Description

Splits up the data into blocks and computes the normalized componentwise maxima with their occurrences for each block

Usage

maxblocks(y,n.blocks=50)

Arguments

y	a matrix representing the data.
n.blocks	the numbers of blocks.

Value

returns a list l including:

l$normalized.max	the normalized maxima (divided by the number of observation in a block
l$classes.max	the partitions that gives which componentwise maxima occur simultaneously

Examples

raw.data<-rCMS(copulas=c(copClayton,copGumbel),
               margins=c(marginLnorm,marginFrechet),
               classes=c(rep(1,10),rep(2,10)),
               params=c(0.5,1,1.5,1.7),n=1000)
data<-maxblocks(raw.data,n.blocks=20)

HiDimMaxStable documentation built on May 29, 2017, 6:20 p.m.