PF_control | R Documentation |
Auxiliary for additional settings with PF_EM
.
PF_control( N_fw_n_bw = NULL, N_smooth = NULL, N_first = NULL, eps = 0.01, forward_backward_ESS_threshold = NULL, method = "AUX_normal_approx_w_cloud_mean", n_max = 25, n_threads = getOption("ddhazard_max_threads"), smoother = "Fearnhead_O_N", Q_tilde = NULL, est_a_0 = TRUE, N_smooth_final = N_smooth, nu = 0L, covar_fac = -1, ftol_rel = 1e-08, averaging_start = -1L, fix_seed = TRUE )
N_fw_n_bw |
number of particles to use in forward and backward filter. |
N_smooth |
number of particles to use in particle smoother. |
N_first |
number of particles to use at time 0 and time d + 1. |
eps |
convergence threshold in EM method. |
forward_backward_ESS_threshold |
required effective sample size to not re-sample in the particle filters. |
method |
method for forward, backward and smoothing filter. |
n_max |
maximum number of iterations of the EM algorithm. |
n_threads |
maximum number threads to use in the computations. |
smoother |
smoother to use. |
Q_tilde |
covariance matrix of additional error term to add to the
proposal distributions. |
est_a_0 |
|
N_smooth_final |
number of particles to sample with replacement from
the smoothed particle cloud with |
nu |
integer with degrees of freedom to use in the (multivariate) t-distribution used as the proposal distribution. A (multivariate) normal distribution is used if it is zero. |
covar_fac |
factor to scale the covariance matrix with. Ignored if the values is less than or equal to zero. |
ftol_rel |
relative convergence tolerance of the mode objective in mode approximation. |
averaging_start |
index to start averaging. Values less then or equal to zero yields no averaging. |
fix_seed |
|
The method
argument can take the following values
bootstrap_filter
for a bootstrap filter.
PF_normal_approx_w_cloud_mean
for a particle filter where a
Gaussian approximation is used using a Taylor
approximation made at the mean for the current particle given the mean of the
parent particles and/or mean of the child particles.
AUX_normal_approx_w_cloud_mean
for an auxiliary particle filter
version of PF_normal_approx_w_cloud_mean
.
PF_normal_approx_w_particles
for a filter similar to
PF_normal_approx_w_cloud_mean
and differs by making a Taylor
approximation at a mean given each sampled parent and/or child particle.
AUX_normal_approx_w_particles
for an auxiliary particle filter
version of PF_normal_approx_w_particles
.
The smoother
argument can take the following values
Fearnhead_O_N
for the smoother in Fearnhead, Wyncoll, and Tawn
(2010).
Brier_O_N_square
for the smoother in Briers, Doucet, and
Maskell (2010).
A list with components named as the arguments.
Gordon, N. J., Salmond, D. J., and Smith, A. F. (1993) Novel approach to nonlinear/non-Gaussian Bayesian state estimation. In IEE Proceedings F (Radar and Signal Processing), (Vol. 140, No. 2, pp. 107-113). IET Digital Library.
Pitt, M. K., and Shephard, N. (1999) Filtering via simulation: Auxiliary particle filters. Journal of the American statistical association, 94(446), 590-599.
Fearnhead, P., Wyncoll, D., and Tawn, J. (2010) A sequential smoothing algorithm with linear computational cost. Biometrika, 97(2), 447-464.
Briers, M., Doucet, A., and Maskell, S. (2010) Smoothing algorithms for state-space models. Annals of the Institute of Statistical Mathematics, 62(1), 61.
PF_EM
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