Hi George,

I have completely forgotten about dr.fuu, I don't see at the moment what it is useful for. Porting the varexo_det stuff to C++ isn't a priority, far from it. I would rather that you clean-up existing k_order_perturbation code. When that is done, I would like you to turn to the Kalman filter, but we will need to do a careful analysis before starting to code. One question will be which matrix implementation to use in the Kalman filter code? Shall we keep using Ondra's TwoD matrices? Shall we build our own (doubtful)? Should we use something like Boost?

Best

Michel

G. Perendia wrote:

Dear Michel

I was thinking of re-using some of the existing 2nd order dr1.m code to determine dr.fuu and the rules for, if any, deterministic exogenous vars (dr.gh??d).

Looking at the code in dr1.m, for both dr.fuu and deterministic exogenous vars, we need hessian and, for the former, jacobian. Shall I retrieve them from k-order-perturbation or is there a more elegant way to get those rules that you can think of? Perhaps we can determine fuu from ghs2 (if not 0) more elegantly but I can not see it as yet.

I however could not find where dr.fuu is used other than internally within dr1.m (and dr11_sparse.m). That could mean that we only need hessian and only infrequently when if we have deterministic exogenous vars.

Best regards

George Mob. +44(0)7951415480 artilogica@btconnect.com