simulate_burninthining_multiple {ERPM}

Simulate burnin thining multiple

Description

Function that simulates the Markov chain for a given model and a set of transitions (the neighborhood), for multiple partitions. It calculates the autocorrelation of statistics for different thinings and the average statistics for different burn-ins.

Usage

simulate_burninthining_multiple(
  partitions,
  presence.tables,
  theta,
  nodes,
  effects,
  objects,
  num.steps,
  neighborhood,
  numgroups.allowed,
  numgroups.simulated,
  sizes.allowed,
  sizes.simulated,
  max.thining,
  verbose = FALSE
)

Arguments

partitions

Observed partitions

presence.tables

to indicate which nodes were present when

theta

Initial model parameters

nodes

Node set (data frame)

effects

Effects/sufficient statistics (list with a vector "names", and a vector "objects")

objects

Objects used for statistics calculation (list with a vector "name", and a vector "object")

num.steps

Number of samples wanted

neighborhood

Way of choosing partitions: probability vector (proba actors swap, proba merge/division, proba single actor move)

numgroups.allowed

vector containing the number of groups allowed in the partition (now, it only works with vectors like num_min:num_max)

numgroups.simulated

vector containing the number of groups simulated

sizes.allowed

Vector of group sizes allowed in sampling (now, it only works for vectors like size_min:size_max)

sizes.simulated

Vector of group sizes allowed in the Markov chain but not necessraily sampled (now, it only works for vectors like size_min:size_max)

max.thining

maximal number of simulated steps in the thining

verbose

logical: should intermediate results during the estimation be printed or not? Defaults to FALSE.

Value

A list