graphicalExtremes (version 0.1.0)

data2mpareto: Data standardization to multivariate Pareto scale

Description

Transforms the data matrix empirically to the multivariate Pareto scale.

Usage

data2mpareto(data, p)

Value

Numeric matrix \(m \times d\), where \(m\) is the number of rows in the original data matrix that are above the threshold.

Arguments

data

Numeric matrix of size \(n\times d\), where \(n\) is the number of observations and \(d\) is the dimension.

p

Numeric between 0 and 1. Probability used for the quantile to threshold the data.

Details

The columns of the data matrix are first transformed empirically to standard Pareto distributions. Then, only the observations where at least one component exceeds the p-quantile of the standard Pareto distribution are kept. Those observations are finally divided by the p-quantile of the standard Pareto distribution to standardize them to the multivariate Pareto scale.

Examples

n <- 20
d <- 4
p <- .8
G <-  cbind(c(0, 1.5, 1.5, 2),
            c(1.5, 0, 2, 1.5),
            c(1.5, 2, 0, 1.5),
            c(2, 1.5, 1.5, 0))

set.seed(123)
my_data = rmstable(n, "HR", d = d, par = G)
data2mpareto(my_data, p)

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