function jumpgarchx u h lambda deltasq theta ek
type real jumpgarchx u h lambda deltasq theta *ek
*
local integer k
local real jsd wt jp
*
compute wt=0.0
compute ek=0.0
compute jumpgarchx=0.0
do k=0,kmax
compute jsd=sqrt(h+k*deltasq)
compute jp =exp(k*log(lambda)-%lngamma(k+1))
compute wt =wt+jp
compute jpu=jp*%density((u-k*theta)/jsd)/jsd
compute jumpgarchx=jumpgarchx+jpu
compute ek=ek+k*jpu
end do k
compute ek=ek*jumpgarchx
compute jumpgarchx=log(jumpgarchx/wt)
end jumpgarchx
TomDoan wrote:There's an earlier post that shows how to compute the expected number of jumps:
viewtopic.php?p=7979#p7979
The change to the GARCH formula is relatively simple given that.
TomDoan wrote:The use of the source file is to simplify the use of that function, which is needed in both of those programs. If you're just doing a single program, you may not need to strip that out.
The trickiest part about using a function inside a FRML is that, in most cases, it somehow depends upon time "T" information. If possible, it's usually simplest to make the time T references in the FRML rather than the function. For instance, in this:
frml logl = u=uf,h=hf,lambda_t=lambda0,deltasq_t=zeta0^2,theta_t=eta0,$
arjigarch(u,h,lambda_t,deltasq_t,theta_t,xi_t)
all six arguments actually refer to something that depends upon the entry number (U is the current residual, H the current GARCH process variance, etc.) which is what everything on that first line is computing. As long as you're still in the FRML definition, U (if U is a series) means U(T), and same for the other. Thus ARJIGARCH and JUMPGARCH and JUMPGARCHX don't actually need to know what time period they're computing.
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