statcvm {CopulaInference}

Goodness-of-fit statistics

Description

Computation of goodness-of-fit statistics (Cramer-von Mises and the Kendall's tau)

Usage

statcvm(object)

Arguments

object

Object of class 'EstBiCop'.

Value

Sn

Cramer-von Mises statistic

Tn

Kendall's statistic

Rn

Spearman's statistic

tauemp

Empirical Kendall's tau

tauth

Kendall's tau of the multilineat theoretical copula

rhoemp

Empirical Spearman's rho

rhoth

Spearman's rho of the multilineat theoretical copula

Y1

Ordered observed values of X1

F1

Empirical cdf of Y1

Y2

Ordered observed values of X2

F2

Empirical cdf of Y2

cpar

Copula parameters

family

Copula family

rotation

Rotation value

n

Sample size

References

Nasri & Remillard (2023). Identifiability and inference for copula-based semiparametric models for random vectors with arbitrary marginal distributions. arXiv 2301.13408.

Examples

set.seed(2)
data = matrix(rpois(20,1),ncol=2)
out0 = EstBiCop(data,"gumbel")
out = statcvm(out0)