run_phase1_multiple {ERPM}

Phase 1 wrapper for multiple observations

Description

Phase 1 wrapper for multiple observations

Usage

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.

Value

a list