simulateSSM: Simulation of a Gaussian State Space Model

In jrnold/KFAS: Kalman Filter and Smoother for Exponential Family State Space Models.

Description

Function simulateSMM simulates states, disturbances or missing observations of the Gaussian state space object conditionally on the data.

Usage

  simulateSSM(object,
    sim = c("states", "disturbances", "observations"),
    nsim = 1, antithetics = FALSE, conditional = TRUE)

Arguments

object	Gaussian state space object.
sim	What to simulate. Note that all the simulations are done independently.
nsim	Number of independent samples. Default is 1.
antithetics	Use antithetic variables in simulation. Default is FALSE.
conditional	Simulations are conditional to data. If FALSE, the initial state α[1] is set to alphahat[1] computed by KFS, and all the observations are removed from the model. Default is TRUE.

Details

Simulation smoother algorithm is from article by J. Durbin and S.J. Koopman (2002).

Function can use two antithetic variables, one for location and other for scale, so output contains four blocks of simulated values which correlate which each other (ith block correlates negatively with (i+1)th block, and positively with (i+2)th block etc.).

References

Durbin J. and Koopman, S.J. (2002). A simple and efficient simulation smoother for state space time series analysis, Biometrika, Volume 89, Issue 3

jrnold/KFAS documentation built on May 19, 2019, 11:55 p.m.