mssm (version 0.1.3)

mssm-smoother: Computes Smoothed Particle Weights for Multivariate State Space Model

Description

Computes smoothed weights using the backward smoothing formula for a mssm object. The k-d dual tree approximation is also used if it used for the mssm object.

Arguments

object

an object of class mssm from mssm-pf.

Value

Same as mssm-pf but where the pf_output's list elements has an additional element called ws_normalized_smooth. This contains the normalized log smoothing weights.

See Also

mssm.

Examples

# NOT RUN {
if(require(Ecdat)){
  # load data and get object to perform particle filtering
  data("Gasoline", package = "Ecdat")

  library(mssm)
  ll_func <- mssm(
    fixed = lgaspcar ~ factor(country) + lincomep + lrpmg + lcarpcap,
    random = ~ 1, family = Gamma("log"), data = Gasoline, ti = year,
    control = mssm_control(N_part = 1000L, n_threads = 1L))

  # run particle filter
  cfix <- c(0.612, -0.015, 0.214, 0.048, -0.013, -0.016, -0.022, 0.047,
            -0.046, 0.007, -0.001, 0.008, -0.117, 0.075, 0.048, -0.054, 0.017,
            0.228, 0.077, -0.056, -0.139)
  pf <- ll_func$pf_filter(
    cfix = cfix, Q = as.matrix(2.163e-05), F. = as.matrix(0.9792),
    disp = 0.000291)

  print(is.null(pf$pf_output[[1L]]$ws_normalized_smooth))
  pf <- ll_func$smoother(pf)
  print(is.null(pf$pf_output[[1L]]$ws_normalized_smooth))
}
# }