[R] numerical solution of functional equations (dynamic stochastic optimization)

[Tamas Papp]

Hi,

I need some help with solving functional equations (Bellman's or
Euler's) with numerical methods.  I have read the relevant books
(Kenneth L Judd: Numerical methods in economics, and some others), but
have no practical experience.

All the examples in these books are in Matlab, but I would prefer R,
since I have been using that for some time and I think that it is
generally much nicer a language.  So program code or advice from
somebody who has used R for solving dynamic stochastic optimization
problems (preferably in economics, but other fields are OK) would be
welcome.

Some specific questions:

1. The state space is 4 dimensional.  I think that I will use splines,
what is the easy way to generate and handle multidimensional spline
basis in R? There are many spline packages in R, which ones would you
recommend for this?

2. Is there a package in R which helps generate orthogonal an
Chebyshev basis?

3. I would like to use quadrature rules to speed up integration (ie
the calculation of expected values), which package would you
recommend?

Again, R code would be especially appreciated: I know some R, but
people on this list present such elegant solutions to use it in ways I
would not have thought of.

Thanks,

Tamas

-- 
Tamás K. Papp
E-mail: tpapp at axelero.hu (preferred, especially for large messages)
        tpapp at westel900.net
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