make_par_values_stops function

make_par_values_stops

helper to remove stops and reduce complexity of make_par_values

make_par_values_stops(
  model,
  alter = "priors",
  x = NA,
  alter_at = NA,
  node = NA,
  label = NA,
  nodal_type = NA,
  param_set = NA,
  given = NA,
  statement = NA,
  join_by = "|",
  param_names = NA,
  distribution = NA,
  normalize = FALSE
)

Arguments

• model: model created with make_model
• alter: character vector with one of "priors" or "param_value" specifying what to alter
• x: vector of real non negative values to be substituted into "priors" or "param_value"
• alter_at: string specifying filtering operations to be applied to parameters_df, yielding a logical vector indicating parameters for which values should be altered. (see examples)
• node: string indicating nodes which are to be altered
• label: string. Label for nodal type indicating nodal types for which values are to be altered. Equivalent to nodal_type.
• nodal_type: string. Label for nodal type indicating nodal types for which values are to be altered
• param_set: string indicating the name of the set of parameters to be altered
• given: string indicates the node on which the parameter to be altered depends
• statement: causal query that determines nodal types for which values are to be altered
• join_by: string specifying the logical operator joining expanded types when statement contains wildcards. Can take values '&' (logical AND) or '|' (logical OR).
• param_names: vector of strings. The name of specific parameter in the form of, for example, 'X.1', 'Y.01'
• distribution: string indicating a common prior distribution (uniform, jeffreys or certainty)
• normalize: logical. If TRUE normalizes such that param set probabilities sum to 1.