get control parameters for DEVI function
AlgoParamsDEVI(
n_params,
param_names = NULL,
n_chains = NULL,
n_iter = 1000,
init_sd = 0.01,
init_center = 0,
n_cores_use = 1,
step_size = NULL,
jitter_size = 1e-06,
parallel_type = "none",
use_QMC = TRUE,
purify = NULL,
quasi_rand_seq = "halton",
n_samples_ELBO = 10,
LRVB_correction = TRUE,
n_samples_LRVB = 25,
neg_inf = -750,
thin = 1,
burnin = 0,
return_trace = FALSE,
crossover_rate = 1
)number of free parameters estimated
optional vector of parameter names
number of particle chains used for optimization, 3*n_params is the default value
number of iterations to run the sampling algorithm, 1000 is default
positive scalar or n_params-dimensional numeric vector, determines the standard deviation of the Gaussian initialization distribution
scalar or n_params-dimensional numeric vector, determines the mean of the Gaussian initialization distribution
number of cores used when using parallelization.
positive scalar, jump size in DE crossover step, default is 2.38/sqrt(2*n_params).
positive scalar, noise is added during crossover step from Uniform(-jitter_size,jitter_size) distribution. 1e-6 is the default value.
string specifying parallelization type. 'none','FORK', or 'PSOCK' are valid values. 'none' is default value.
logical, if true, a quasi-Monte Carlo estimator is used to estimate ELBO during optimization. default is TRUE.
an integer, every 'purify'-th iteration, the Monte Carlo estimator of the ELBO is recalculated. This can help deal with noisy and outlier estimates of the ELBO. Default value is 25. If use_QMC is TRUE, purification is disabled as it is redundant.
type of low discrepancy sequence used for quasi Monte Carlo integration, either 'sobol' or 'halton'. LRVB correction always use QMC. Default is 'sobol'.
number of samples used for the Monte Carlo estimator of the ELBO (the objective function). default is 10.
logical, if true, LRVB covariance correction (Giordano, Brodderick, & Jordan 2018; Galdo, Bahg, & Turner 2020) is attempted.
number of samples used for LRVB correction. default is 25.
if density for a given value of theta is numerically 0 for q, this value is assigned for log density. This helps with numeric stability of algorithm. Default value is -750.
positive integer, only every 'thin'-th iteration will be stored. Default value is 1. Increasing thin will reduce the memory required, while running algorithm for longer.
number of initial iterations to discard. Default value is 0.
logical, if true, function returns particle trajectories. This is helpful for diagnosing convergence or debugging model code. Function will return an iteration/thin $x$ n_chains $x$ n_params array and the estimated ELBO of each particle in a iteration/thin x n_chains array.
number on the interval (0,1]. Determines the probability a parameter on a chain is updated on a given crossover step, sampled from a Bernoulli distribution.
list of control parameters for the DEVI function