subrank-package: Computes Copula using Ranks and Subsampling

In subrank: Computes Copula using Ranks and Subsampling

Computes Copula using Ranks and Subsampling

Description

Estimation of copula using ranks and subsampling. The main feature of this method is that simulation studies show a low sensitivity to dimension, on realistic cases.

Details

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Taking a sample, its dimension, and a sub-sample size, allows to estimate a discretized copula. This object has interesting features: convergence to copula, robustness with respect to dimension.

Author(s)

Jerome Collet

Maintainer: Jerome Collet <[e-mail]>

Examples

lon <- 31
a <- 2.85
x <- rnorm(lon)
y = a*x^2+rnorm(lon)
tablo = as.data.frame(cbind(x,y))
c=corc(tablo,c(1,2),8)
desscop(c,1,2)

subrank documentation built on April 6, 2023, 1:11 a.m.