Learn R Programming
bssm (version 1.0.0)

importance_sample: Importance Sampling from non-Gaussian State Space Model

Description

Returns nsim samples from the approximating Gaussian model with corresponding (scaled) importance weights.

Usage

importance_sample(model, nsim, use_antithetic, max_iter, conv_tol, seed, ...)
# S3 method for nongaussian
importance_sample(
  model,
  nsim,
  use_antithetic = TRUE,
  max_iter = 100,
  conv_tol = 1e-08,
  seed = sample(.Machine$integer.max, size = 1),
  ...
)

Arguments

model

of class bsm_ng, ar1_ng svm, ssm_ung, or ssm_mng.

nsim

Number of samples.

use_antithetic

Logical. If TRUE (default), use antithetic variable for location in simulation smoothing. Ignored for ssm_mng models.

max_iter

Maximum number of iterations used for the approximation.

conv_tol

Convergence threshold for the approximation. Approximation is claimed to be converged when the mean squared difference of the modes is less than conv_tol.

seed

Seed for the random number generator.

...

Ignored.