gridsearch_burnin_single function

Grid - search burnin single

Function that can be used to find a good length for the burn-in of the Markov chain for a given model and differents sets of transitions in the chain (the neighborhoods). For each neighborhood, it draws a chain and calculates the mean statistics for different burn-ins.

gridsearch_burnin_single(
  partition,
  theta,
  nodes,
  effects,
  objects,
  num.steps,
  neighborhoods,
  numgroups.allowed,
  numgroups.simulated,
  sizes.allowed,
  sizes.simulated,
  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: = NULL, # 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)
• parallel: False, to run different neighborhoods in parallel
• cpus: Equal to 1

Returns

all simulations