*
* Example from section 9.6
* Approximate methods for modelling stochastic volatility
* ??? Parameterization???
*
open data sv.dat
data(format=free,skip=1) 1 945 xrate
*
set ysq = log(xrate**2)+log(2)-%digamma(1)
*
nonlin phi sw sv logsigsq
compute phi=.9,sw=.011,sv=1.0
dlm(method=bfgs,y=ysq-logsigsq,a=phi,c=1.0,sw=sw,sv=sv,$
   sx0=sw/(1-phi**2),type=smooth) 1 945 states
*
set stderr = exp(.5*states(t)(1))
graph(footer="Figure 9.12 Estimated volatility for the Pound Series")
# stderr
*
nonlin phi gamma sw sv
dlm(method=bfgs,y=ysq,a=phi,z=gamma,c=1.0,sw=sw,sv=sv,$
   sx0=sw/(1-phi**2),x0=gamma/(1-phi),type=smooth) 1 945 states
*
set stderr = exp(.5*states(t)(1))
graph(footer="Figure 9.12 Estimated volatility for the Pound Series")
# stderr