AlgoParamsDEVI: AlgoParamsDEVI

In DEBBI: Differential Evolution-Based Bayesian Inference

AlgoParamsDEVI

Description

get control parameters for DEVI function

Usage

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
)

Arguments

n_params	number of free parameters estimated
param_names	optional vector of parameter names
n_chains	number of particle chains used for optimization, 3*n_params is the default value
n_iter	number of iterations to run the sampling algorithm, 1000 is default
init_sd	positive scalar or n_params-dimensional numeric vector, determines the standard deviation of the Gaussian initialization distribution
init_center	scalar or n_params-dimensional numeric vector, determines the mean of the Gaussian initialization distribution
n_cores_use	number of cores used when using parallelization.
step_size	positive scalar, jump size in DE crossover step, default is 2.38/sqrt(2*n_params).
jitter_size	positive scalar, noise is added during crossover step from Uniform(-jitter_size,jitter_size) distribution. 1e-6 is the default value.
parallel_type	string specifying parallelization type. 'none','FORK', or 'PSOCK' are valid values. 'none' is default value.
use_QMC	logical, if true, a quasi-Monte Carlo estimator is used to estimate ELBO during optimization. default is TRUE.
purify	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.
quasi_rand_seq	type of low discrepancy sequence used for quasi Monte Carlo integration, either 'sobol' or 'halton'. LRVB correction always use QMC. Default is 'sobol'.
n_samples_ELBO	number of samples used for the Monte Carlo estimator of the ELBO (the objective function). default is 10.
LRVB_correction	logical, if true, LRVB covariance correction (Giordano, Brodderick, & Jordan 2018; Galdo, Bahg, & Turner 2020) is attempted.
n_samples_LRVB	number of samples used for LRVB correction. default is 25.
neg_inf	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.
thin	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.
burnin	number of initial iterations to discard. Default value is 0.
return_trace	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.
crossover_rate	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.

Value

list of control parameters for the DEVI function

DEBBI documentation built on May 17, 2022, 5:08 p.m.