fit.tcopula {QRMlib}R Documentation

Fit t Copula

Description

fit t copula to pseudo-copula data

Usage

fit.tcopula(Udata)

Arguments

Udata matrix of pseudo-copula data where rows are vector observations with all values in unit interval

Details

see pages 235-236 of QRM

Value

list containing parameter estimates and details of fit

See Also

fit.gausscopula, fit.Archcopula2d

Examples

data(ftse100);
data(smi);
TS1 <- window(ftse100, "1990-11-09", "2004-03-25");
TS1Augment <- alignDailySeries(TS1, method="before");
TS2Augment <- alignDailySeries(smi, method="before");
INDEXES.RAW <- merge(TS1Augment,TS2Augment);
#Cleanup:
rm(TS1, TS1Augment, TS2Augment);
INDEXES <- mk.returns(INDEXES.RAW);
PARTIALINDEXES <- window(INDEXES, "1994-01-01", "2003-12-31");
#Now create a data matrix from the just-created timeSeries 
data <- seriesData(PARTIALINDEXES);
#Keep only the data items which are non-zero for both smi and ftse100
data <- data[data[,1]!=0 & data[,2] !=0,];
# Construct pseudo copula data. The 2nd parameter is MARGIN=2 
#when applying to columns and 1 applied to rows. Hence this says to
#apply the 'edf()' empirical distribtion function() to the columns
#of the data. 
Udata <- apply(data,2,edf,adjust=1);
#Fit a t-copula to the data: 
mod.t <- fit.tcopula(Udata); 
mod.t; 

[Package QRMlib version 1.4.4 Index]