mssm_control {mssm} | R Documentation |
Auxiliary function for mssm
.
mssm_control(N_part = 1000L, n_threads = 1L, covar_fac = 1.2, ftol_rel = 1e-06, nu = 8, what = "log_density", which_sampler = "mode_aprx", which_ll_cp = "no_aprx", seed = 1L, KD_N_max = 10L, aprx_eps = 0.001, ftol_abs = 1e-04, ftol_abs_inner = 1e-04, la_ftol_rel = -1, la_ftol_rel_inner = -1, maxeval = 10000L, maxeval_inner = 10000L, use_antithetic = FALSE)
N_part |
integer greater than zero for the number of particles to use. |
n_threads |
integer greater than zero for the number of threads to use. |
covar_fac |
positive numeric scalar used to scale the covariance matrix in the proposal distribution. |
ftol_rel |
positive numeric scalar with convergence threshold passed
to |
nu |
degrees of freedom to use for the multivariate
t-distribution that is used as the proposal distribution. A
multivariate normal distribution is used if |
what |
character indicating what to approximate. |
which_sampler |
character indicating what type of proposal
distribution to use. |
which_ll_cp |
character indicating what type of computation should be
performed in each iteration of the particle filter. |
seed |
integer with seed to pass to |
KD_N_max |
integer greater than zero with the maximum number of particles to include in each leaf of the two k-d trees if the dual k-d trees method is used. |
aprx_eps |
positive numeric scalar with the maximum error if the dual k-d tree method is used. |
ftol_abs, ftol_abs_inner, la_ftol_rel, la_ftol_rel_inner, maxeval, maxeval_inner |
scalars passed to |
use_antithetic |
logical which is true if antithetic variables should be used. |
mssm
.
See the README of the package for details of the dual k-d tree method at https://github.com/boennecd/mssm.
library(mssm) str(mssm_control()) str(mssm_control(N_part = 2000L))