preferentialSampling: preferentialSampling

In brianconroy/preferential_surveillance: Analysis of Disease Surveillance Data under Preferential Sampling

Description

preferentialSampling

Usage

preferentialSampling(
  data,
  d,
  n.sample,
  burnin,
  L_w,
  L_ca,
  L_co,
  L_a_ca,
  L_a_co,
  proposal.sd.theta = 0.3,
  m_aca = 2000,
  m_aco = 2000,
  m_ca = 700,
  m_co = 700,
  m_w = 700,
  target_aca = 0.75,
  target_aco = 0.75,
  target_ca = 0.75,
  target_co = 0.75,
  target_w = 0.75,
  target_loc = 0.75,
  self_tune_w = TRUE,
  self_tune_aca = TRUE,
  self_tune_aco = TRUE,
  self_tune_ca = TRUE,
  self_tune_co = TRUE,
  self_tune_loc = TRUE,
  delta_w = NULL,
  delta_aca = NULL,
  delta_aco = NULL,
  delta_ca = NULL,
  delta_co = NULL,
  delta_loc = NULL,
  beta_ca_initial = NULL,
  beta_co_initial = NULL,
  alpha_ca_initial = NULL,
  alpha_co_initial = NULL,
  beta_loc_initial = NULL,
  theta_initial = NULL,
  phi_initial = NULL,
  w_initial = NULL,
  prior_phi,
  prior_theta,
  prior_alpha_ca_var,
  prior_alpha_co_var
)

Arguments

data	List. Data input containing case, control counts, covariates.
d	Matrix. Distance matrix for grid cells in study region.
n.sample	Numeric. Number of MCMC samples to generate.
burnin	Numeric. Number of MCMC samples to discard as burnin.
L_w	Numeric. HMC simulation length parameter for spatial random effects.
L_ca	Numeric. HMC simulation length parameter for case covariates.
L_co	Numeric. HMC simulation length parameter for control covariates.
L_a_ca	Numeric. HMC simulation length parameter for case preferential sampling parameter.
L_a_co	Numeric. HMC simulation length parameter for control preferential sampling parameter.
proposal.sd.theta	Numeric. Standard deviation of proposal distribution for spatial range parameter.
m_aca	Numeric. Number of samples to apply self tuning for case preferential sampling parameter.
m_aco	Numeric. Number of samples to apply self tuning for control preferential sampling parameter.
m_ca	Numeric. Number of samples to apply self tuning for case covariates.
m_co	Numeric. Number of samples to apply self tuning for control covariates.
m_w	Numeric. Number of samples to apply self tuning for spatial random effects.
target_aca	Numeric. Target acceptance rate for case preferential sampling parameter.
target_aco	Numeric. Target acceptance rate for control preferential sampling parameter.
target_ca	Numeric. Target acceptance rate for case covariates.
target_co	Numeric. Target acceptance rate for control covariates.
target_w	Numeric. Target acceptance rate for spatial random effects.
target_loc	Numeric. Target acceptance rate for locational covariates.
self_tune_w	Logical. Whether to apply self tuning for spatial random effects.
self_tune_aca	Logical. Whether to apply self tuning for case preferential sampling paramter.
self_tune_aco	Logical. Whether to apply self tuning for control preferential sampling paramter.
self_tune_ca	Logical. Whether to apply self tuning for case covariates.
self_tune_co	Logical. Whether to apply self tuning for control covariates.
self_tune_loc	Logical. Whether to apply self tuning for locational covariates.
delta_w	Numeric. Required if self_tune_w is FALSE. HMC step size for spatial random effects.
delta_aca	Numeric. Required if self_tune_w is FALSE. HMC step size for case preferential sampling parameter.
delta_aco	Numeric. Required if self_tune_w is FALSE. HMC step size for control preferential sampling parameter.
delta_ca	Numeric. Required if self_tune_w is FALSE. HMC step size for case covariates.
delta_co	Numeric. Required if self_tune_w is FALSE. HMC step size for control covariates.
delta_loc	Numeric. Required if self_tune_w is FALSE. HMC step size for locational covariates.
beta_ca_initial	Numeric. Initial MCMC value for case covariate parameter.
beta_co_initial	Numeric. Initial MCMC value for control covariate parameter.
alpha_ca_initial	Numeric. Initial MCMC value for case preferential sampling parameter.
alpha_co_initial	Numeric. Initial MCMC value for control preferential sampling parameter.
beta_loc_initial	Numeric. Initial MCMC value for locational covariate parameter.
theta_initial	Numeric. Initial MCMC value for spatial range parameter.
phi_initial	Numeric. Initial MCMC value for spatial marginal variance parameter.
w_initial	Numeric. Initial MCMC value for spatial random effects.
prior_phi	List. Shape and scale values for prior distribution (Inverse Gamma) of marginal variance.
prior_theta	List. Shape and scale values for prior distribution (Gamma) of spatial range.
prior_alpha_ca_var	List. Prior (Independent Normal) variance of case covariates.
prior_alpha_co_var	List. Prior (Independent Normal) variance of control covariates.

Value

List containing posterior samples and associated tuning values.

brianconroy/preferential_surveillance documentation built on Nov. 23, 2021, 5:51 a.m.