StatsFit: Fit Data

In bfw: Bayesian Framework for Computational Modeling

Fit Data

Description

Apply latent or observed models to fit data (e.g., SEM, CFA, mediation)

Usage

StatsFit(
  latent = NULL,
  latent.names = NULL,
  observed = NULL,
  observed.names = NULL,
  additional = NULL,
  additional.names = NULL,
  DF,
  params = NULL,
  job.group = NULL,
  initial.list = list(),
  model.name,
  jags.model,
  custom.model = NULL,
  run.ppp = FALSE,
  run.robust = FALSE,
  ...
)

Arguments

latent	latenr variables, Default: NULL
latent.names	optional names for for latent variables, Default: NULL
observed	observed variable(s), Default: NULL
observed.names	optional names for for observed variable(s), Default: NULL
additional	supplemental parameters for fitted data (e.g., indirect pathways and total effect), Default: NULL
additional.names	optional names for supplemental parameters, Default: NULL
DF	data to analyze
params	define parameters to observe, Default: NULL
job.group	for some hierarchical models with several layers of parameter names (e.g., latent and observed parameters), Default: NULL
initial.list	initial values for analysis, Default: list()
model.name	name of model used
jags.model	specify which module to use
custom.model	define a custom model to use (e.g., string or text file (.txt), Default: NULL
run.ppp	logical, indicating whether or not to conduct ppp analysis, Default: FALSE
run.robust	logical, indicating whether or not robust analysis, Default: FALSE
...	further arguments passed to or from other methods

See Also

complete.cases

bfw documentation built on March 18, 2022, 6:19 p.m.