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/*
* Copies all the estimation results nicely into the bundle.
*/
function void gig_packResults(bundle *mod, scalar err, matrix thetahat,
series *h, series *e,
matrix inipar, matrix Sigma, matrix crit)
mod.errcode = err
if (err == 0)
theta = mod.coeff
sel = mod.active
theta[sel] = thetahat
mod.inipar = inipar
vk = mod.vk
if (vk>1) && (mod.vX_QR == 1)
J = I(rows(Sigma))
mk = mod.mk
sel = seq(mk+1, mk+vk)
invR = inv(mod.vX_R)
J[sel,sel] = invR
theta[sel] = invR * theta[sel]
Sigma = qform(J, Sigma)
endif
mod.coeff = theta
mod.vcv = Sigma
mod.stderr = sqrt(diag(Sigma))
mod.h = h
mod.uhat = e
mod.stduhat = e/sqrt(h)
mod.criteria = crit
endif
end function
/*
Performs garch-like parameters estimation: the parameters must have
already been initialised somehow.
*/
function scalar gig_estimate(bundle *model, int verbose[0:2:1])
# verbose = 0 -> quiet
# verbose = 1 -> show output
# verbose = 2 -> show iterations
scalar garchType = model.type
t1 = model.t1
t2 = model.t2
smpl t1 t2
if garchType <= 7 #APARCH & EGARCH
scalar err = do_mle(&model, verbose==2)
elif garchType == 8
# GARCH-in-Mean
# Not yet, Buster!
# if verbose > 1
# printParList( parIndex, parList, rows(distrInit))
# printf "Proceeding with GARCH-in-mean by Engle et al. estimation.\n\n"
# endif
# ret = garchmean( depVar, meanX, lagOrders, garchInit, distrType,\
# distrInit, verbose, vcv)
printf "Not yet, Buster!\n"
endif
if model.scale != 1
s = model.scale
adjust_for_scale(&model, 1/s)
endif
if (verbose>0)
gig_print(&model)
endif
return err
end function
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