dlmBSample {dlm}

Draw from the posterior distribution of the state vectors

Description

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

Usage

dlmBSample(modFilt)

Arguments

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

Details

The calculations are based on singular value decomposition.

Value

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.

Author(s)

Giovanni Petris [e-mail]

References

Giovanni Petris (2010), An R Package for Dynamic Linear Models. Journal of Statistical Software, 36(12), 1-16. https://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

See also dlmFilter

Examples

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)