fit.mNH {QRMlib} | R Documentation |
fits multivariate NIG or hyperbolic distribution using variant of EM algorithm
fit.mNH(data, symmetric=FALSE, case="NIG", kvalue=NA, nit=2000, tol=1e-10)
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 |
see pages 81-83 in QRM
list containing parameter estimates, standard errors and details of fit
documentation by Scott Ulman for R-language distribution
fit.mst
,
fit.NH
,
EMupdate
,
MCECMupdate
,
MCECM.Qfunc
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");