[R-SIG-Finance] mean reverting model

[rechtsteiner at bgki.net]

dear list members,

i'm trying to estimate the following two regressions:

(I) v_t - v_t-1 = c*(v_t-1 - v_f) + s_t

where v_t and v_t-1 are market volatility at t resp. t-1; c ist the
persistence volatility parameter, v_f the long-run fundamental volatility
and s_t are volatility surprises.
parameters to estimate are c and v_f.

(II) b_t(z_t) = m + f*(b_t-1(z_t) - m) + k*z_t
where the b_t(z_t) are estimated in a seperate regression;
parameters to be estimated are m, the mean reverting beta term, the
persistence parameter f and the sensitivities k of b towards z.

these equations are used in risk and beta anatomy in the hedge fund
industry (savona 2008).

my problem is, that i don't know how to estimate the two equations in R. i
have searched Rsitesearch, google,.. for many hours and didn't find
anything.

could you please give me a hint?

cheers,
josuah