run_phase1_multiple function

Phase 1 wrapper for multiple observations

run_phase1_multiple(
  partitions,
  startingestimates,
  z.obs,
  presence.tables,
  nodes,
  effects,
  objects,
  burnin,
  thining,
  gainfactor,
  a.scaling,
  r.truncation.p1,
  length.p1,
  neighborhood,
  fixed.estimates,
  numgroups.allowed,
  numgroups.simulated,
  sizes.allowed,
  sizes.simulated,
  parallel = FALSE,
  cpus = 1,
  verbose = FALSE
)

Arguments

• partitions: observed partitions
• startingestimates: vector containing initial parameter values
• z.obs: observed statistics
• presence.tables: data frame to indicate which times nodes are present in the partition
• 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")
• burnin: integer for the number of burn-in steps before sampling
• thining: integer for the number of thining steps between sampling
• gainfactor: gain factor (useless now)
• a.scaling: scaling factor
• r.truncation.p1: truncation factor (for stability)
• length.p1: number of samples for phase 1
• neighborhood: vector for the probability of choosing a particular transition in the chain
• fixed.estimates: if some parameters are fixed, list with as many elements as effects, these elements equal a fixed value if needed, or NULL if they should be estimated
• 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 necessarily sampled (now, it only works for vectors like size_min:size_max)
• parallel: boolean to indicate whether the code should be run in parallel
• cpus: number of cpus if parallel = TRUE
• verbose: logical: should intermediate results during the estimation be printed or not? Defaults to FALSE.

Returns

a list