[R] Setting up a State Space Model in dlm
Gavin Simpson
gavin.simpson at ucl.ac.uk
Fri Jun 10 09:22:52 CEST 2011
On Tue, 2011-06-07 at 17:24 +0100, Michael Ash wrote:
> This question pertains to setting up a model in the package "dlm"
> (dynamic linear models,
> http://cran.r-project.org/web/packages/dlm/index.html
The author of the dlm package has just published a paper on state space
models in R including details on setting up dlm:
http://www.jstatsoft.org/v41/i04
That might help with your question - I haven't seen a reply on list, but
am unable to help answer it either.
HTH
G
> I have read both the vignette and "An R Package for Dynamic Linear
> Models" (http://www.jstatsoft.org/v36/i12/paper), both of which are
> very helpful. There is also some discussion at
> https://stat.ethz.ch/pipermail/r-help/2009-May/198463.html
>
> I have what I think is a relatively straightforward state-space model
> but am unable to translate it into the terms of dlm. It would be
> very helpful to get a basic dlm setup for the problem and I would
> guess that I can then modify it with more lags, etc., etc.
>
> The main equation is
> pi[t] = a * pi[t-1] + b*(U[t] - UN[t]) + e[t]
>
> (see http://chart.apis.google.com/chart?cht=tx&chl=%5Cpi_t=a%5Cpi_{t-1}%2bb%28U_t-U^N_{t}%29%2Be_t
> for a pretty version)
>
> with pi and U observed, a and b fixed coefficients, and e a
> well-behaved error term (gaussian, say, variance unknown).
> The object of interest is the unobserved and time-varying component UN
> which evolves according to
>
> UN[t] = UN[t-1] + w[t]
>
> (see http://chart.apis.google.com/chart?cht=tx&chl=U%5EN_%7Bt%7D%20=%20U%5EN_%7Bt-1%7D%20%2B%20%5Cepsilon_t
> for a pretty version)
> that is, a random walk with well-behaved error term with var(w) known
> (or assumed).
>
> I'm interested in the estimates of a and b and also in estimating the
> time series of UN.
>
> Note that the term b*(U[t] - UN[t]) makes this a nonlinear model.
>
> Below is code that does not work as expected. I see the model as
> having four parameters, a, b, var(e), and UN. (Or do I have a
> parameter UN[t] for every period?)
>
> I do not fully understand the dlm syntax. Is FF specified properly?
> What should X look like? How does m0 relate to parm()?
>
>
> I would be grateful if someone would be willing to glance at the code.
> Thanks. Michael
>
> library(quantmod)
> library(dlm)
> ## Get and organize the data
> getSymbols("UNRATE",src="FRED") ## Unemployment rate
> getSymbols("GDPDEF",src="FRED") ## Quarterly GDP Implicit Price Deflator
> u <- aggregate(UNRATE,as.yearqtr,mean)
> gdpdef <- aggregate(GDPDEF,as.yearqtr,mean)
> pi <- diff(log(gdpdef))*400
> pilag <- lag(pi,-1)
> tvnairu <- cbind(pi,pilag,u)
> tvnairu.df <- subset(data.frame(tvnairu), !is.na(pi) & !is.na(u) &
> !is.na(pilag))
>
>
> ## First attempt
> buildNAIRU <- function(x) {
> modNAIRU <- dlm(FF=t(matrix(c(1,1,1,0))),
> GG=diag(4),
> W=matrix(c(0,0,0,0, 0,0,0,0, 0,0,0.04,0, 0,0,0,0),4,4),
> V=exp(x[4]), m0=rep(0,4), C0=diag(1e07,4),
> JFF = t(matrix(c(1,1,0,0))),
> X=cbind( tvnairu.df$pilag, tvnairu.df$u))
> return(modNAIRU)
> }
>
> (fitNAIRU <- dlmMLE(tvnairu.df$pi, parm=c(0,0,0,0) , build=buildNAIRU,
> hessian=TRUE, control=list(maxit=500)))
> (dlmNAIRU <- buildNAIRU(fitNAIRU$par))
>
>
> ## Second attempt
> buildNAIRU <- function(x) {
> modNAIRU <- dlm(FF=t(matrix(c(1,1,0,0))),
> GG=diag(4),
> W=matrix(c(0,0,0,0, 0,0,0,0, 0,0,0.04,0, 0,0,0,0 ),4,4),
> V=exp(x[4]), m0=c(0.7,-0.3,5,1), C0=diag(100,4),
> JFF = t(matrix(c(1,1,0,0))),
> X=cbind( tvnairu.df$pilag, tvnairu.df$u - x[3] ))
> return(modNAIRU)
> }
>
> (fitNAIRU <- dlmMLE(tvnairu.df$pi, parm=c(0,0,0,0) , build=buildNAIRU,
> hessian=TRUE, control=list(maxit=500)))
> (dlmNAIRU <- buildNAIRU(fitNAIRU$par))
>
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Dr. Gavin Simpson [t] +44 (0)20 7679 0522
ECRC, UCL Geography, [f] +44 (0)20 7679 0565
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