sampler.iglm: Constructor for a iglm Sampler

In iglm: Regression under Interference in Connected Populations

Constructor for a iglm Sampler

Description

Creates an object of class 'sampler.iglm' (and 'R6') which holds all parameters controlling the MCMC sampling process for 'iglm' models. This includes global settings like the number of simulations and burn-in, as well as references to specific samplers for the network ('z') and attribute ('x', 'y') components.

This function provides a convenient way to specify these settings before passing them to the 'iglm' constructor or simulation functions.

Usage

sampler.iglm(
  sampler_x = NULL,
  sampler_y = NULL,
  sampler_z = NULL,
  n_simulation = 100,
  n_burn_in = 10,
  init_empty = TRUE,
  seed = NA,
  cluster = NULL,
  file = NULL
)

Arguments

sampler_x	An object of class 'sampler.net.attr' (created by 'sampler.net.attr()') specifying how to sample the 'x_attribute'. If 'NULL' (default), default 'sampler.net.attr()' settings are used.
sampler_y	An object of class 'sampler.net.attr' specifying how to sample the 'y_attribute'. If 'NULL' (default), default settings are used.
sampler_z	An object of class 'sampler.net.attr' specifying how to sample the 'z_network' ties *within* the defined neighborhood/overlap region. If 'NULL' (default), default settings are used.
n_simulation	(integer) The number of independent samples to generate after the burn-in period. Default: 100. Must be non-negative.
n_burn_in	(integer) The number of MCMC iterations to discard at the start for burn-in. Default: 10. Must be non-negative.
init_empty	(logical) If 'TRUE' (default), initialize the MCMC chain from an empty state.
seed	(integer or 'NA') A single integer seed set once before sampling begins to ensure reproducibility. If 'NA' (default), a random seed is generated automatically.
cluster	A parallel cluster object (e.g., from 'parallel::makeCluster()') for parallel simulations. If 'NULL' (default), simulations run sequentially.
file	(character or 'NULL') If provided, loads the sampler state from the specified .rds file instead of initializing from parameters.

Value

An object of class 'sampler.iglm' (and 'R6').

See Also

'sampler.net.attr', 'iglm', 'control.iglm'

Examples

n_actor <- 50
sampler_new <- sampler.iglm(
  n_burn_in = 100, n_simulation = 10,
  seed = 42,
  sampler_x = sampler.net.attr(n_proposals = n_actor * 10),
  sampler_y = sampler.net.attr(n_proposals = n_actor * 10),
  sampler_z = sampler.net.attr(n_proposals = n_actor^2, tnt = TRUE),
  init_empty = FALSE
)
sampler_new
sampler_new$seed
sampler_new$set_n_simulation(100)
sampler_new$n_simulation

iglm documentation built on April 23, 2026, 5:07 p.m.