Hello everyone. Apologies for cross posting with R-help and for a possible relationship with the thread "Bayesian estimation of jump-diffusion processes and self-exciting counting processes".
I have an interest in fitting jump diffusion AR(p) processes (which will likely form part of a Garch model with Normal errors). Does anyone know of some R code that will allow this please, hopefully using max likelihood (or similar) methods?
I'm currently using WinBUGS and RWinBUGS to utilise a Bayesian approach but my dataset is quite large (n=17,000 being half-hourly electricity prices for a year) and, not surprisingly, the routines have issues with execution time and program stability.
Many thanks,
Ross Bowden,
Synergy Energy,
Perth, Western Australia.
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