bayesSSM (version 0.7.1)

.pilot_run: Pilot Run for Particle Filter Tuning

Description

This internal function repeatedly evaluates the particle filter in order to estimate the variance of the log-likelihoods and to compute a recommended target number of particles for the Particle Marginal Metropolis Hastings (PMMH) algorithm.

Usage

.pilot_run(
  pf_wrapper,
  y,
  pilot_n,
  pilot_reps,
  init_fn,
  transition_fn,
  log_likelihood_fn,
  obs_times = NULL,
  resample_fn = NULL,
  ...
)

Value

A list containing:

variance_estimate

The estimated variance of the log-likelihoods from the pilot run.

target_N

The number of particles used in PMMH algorithm.

pilot_loglikes

A numeric vector of log-likelihood values computed during the run.

Arguments

pilot_n

An integer specifying the initial number of particles to use.

pilot_reps

An integer specifying the number of repetitions for the pilot run.

Details

The function performs pilot_reps evaluations of the particle filter using the provided parameter vector theta. It then estimates the variance of the log-likelihoods and scales the initial particle number by this variance. The final number of particles is taken as the ceiling of the scaled value with a minimum of 50 and a maximum of 1000.