fit.mNH {QRMlib}R Documentation

Fit Multivariate NIG or Hyperbolic Distribution

Description

fits multivariate NIG or hyperbolic distribution using variant of EM algorithm

Usage

fit.mNH(data, symmetric=FALSE, case="NIG", 
     kvalue=NA, nit=2000, tol=1e-10)

Arguments

data matrix of data where rows are vector observations; common example is data.hyp.5d
symmetric whether symmetric case should be fitted; default is FALSE
case whether NIG ("NIG") or hyperbolic ("hyp") should be fitted
kvalue value to which to constrain determinant of dispersion matrix
nit maximum number of iterations
tol tolerance for convergence

Details

see pages 81-83 in QRM

Value

list containing parameter estimates, standard errors and details of fit

Author(s)

documentation by Scott Ulman for R-language distribution

See Also

fit.mst, fit.NH, EMupdate, MCECMupdate, MCECM.Qfunc

Examples

data(DJ);
Ret.DJ <- mk.returns(DJ); 
window1.start <- timeDate("01/01/1993",format="%m/%d/%Y"); 
window1.end <-  timeDate("12/31/2000", format="%m/%d/%Y"); 
sample1 <- (seriesPositions(Ret.DJ) > window1.start & 
            seriesPositions(Ret.DJ) < window1.end); 
selection1 <- c("AXP","EK","BA","C","KO","MSFT",
                "HWP","INTC","JPM","DIS"); 
DJ30daily <- Ret.DJ[sample1,selection1]; 
DJ30weekly <- aggregateWeeklySeries(DJ30daily, FUNC= colSums);
mod.NIG <- fit.mNH(DJ30weekly,symmetric=FALSE,case="NIG"); 

[Package QRMlib version 1.4.4 Index]