gridsearch_burninthining_single {ERPM}

Grid - search burnin thining single

Description

Function that simulates the Markov chain for a given model and several sets of transitions (the neighborhoods), for a single partition. For each neighborhood, it calculates the autocorrelation of statistics for different thinings and the average statistics for different burn-ins. Then the best neighborhood can be selected along with good values for burn-in and thining

Usage

gridsearch_burninthining_single(
  partition,
  theta,
  nodes,
  effects,
  objects,
  num.steps,
  neighborhoods,
  numgroups.allowed,
  numgroups.simulated,
  sizes.allowed,
  sizes.simulated,
  max.thining,
  parallel = FALSE,
  cpus = 1
)

Arguments

partition

A partition (vector)

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

neighborhoods

List of probability vectors (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

Where to stop adding thining

parallel

False, to run different neighborhoods in parallel

cpus

Equal to 1

Value

list