dlmBSample: Draw from the posterior distribution of the state vectors
In dlm: Bayesian and Likelihood Analysis of Dynamic Linear Models

Description Usage Arguments Details Value Author(s) References See Also Examples

The function simulates one draw from the posterior distribution of the state vectors.

1	dlmBSample(modFilt)

modFilt

a list, typically the ouptut from dlmFilter, with elements m, U.C, D.C, a, U.R, D.R (see the value returned by dlmFilter), and mod The latter is an object of class "dlm" or a list with elements GG, W and, optionally, JGG, JW, and X

The calculations are based on singular value decomposition.

The function returns a draw from the posterior distribution of the state vectors. If m is a time series then the returned value is a time series with the same tsp, otherwise it is a matrix or vector.

Giovanni Petris GPetris@uark.edu

Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. http://www.jstatsoft.org/v36/i12/.
Petris, Petrone, and Campagnoli, Dynamic Linear Models with R, Springer (2009).
West and Harrison, Bayesian forecasting and dynamic models (2nd ed.), Springer (1997).

See also dlmFilter

nileMod <- dlmModPoly(1, dV = 15099.8, dW = 1468.4)
nileFilt <- dlmFilter(Nile, nileMod)
nileSmooth <- dlmSmooth(nileFilt) # estimated "true" level
plot(cbind(Nile, nileSmooth$s[-1]), plot.type = "s",
     col = c("black", "red"), ylab = "Level",
     main = "Nile river", lwd = c(2, 2)) 
for (i in 1:10) # 10 simulated "true" levels 
    lines(dlmBSample(nileFilt[-1]), lty=2)