fit.tcopula.rank {QRMlib}R Documentation

Fit t Copula Using Rank Correlations

Description

fits t copula to pseudo-copula data

Usage

fit.tcopula.rank(Udata, method="Kendall")

Arguments

Udata matrix of pseudo-copula data where rows are vector observations with all values in unit interval
method method to use for calculating rank correlations; default is "Kendall", which is theoretically justified

Details

see pages 229-231 of QRM

Value

list containing parameter estimates and details of fit

See Also

fit.tcopula, fit.gausscopula, fit.Archcopula2d

Examples

# Multivariate Fitting with Gauss and t: Simulation
# Create an equicorrelation matrix:
P <- equicorr(3,0.6);
set.seed(113);
#Generate a new set of random data from a t-copula (10df) with the same Sigma matrix:
Udatasim2 <- rcopula.t(1000,df=10,Sigma=P);
#Now fit the copula to the simulated data using (Kendall) rank correlations
#and the fit.tcopula.rank() method:
mod.t2 <- fit.tcopula.rank(Udatasim2);
mod.t2;

[Package QRMlib version 1.4.4 Index]