make_par_values_stops: make_par_values_stops

In CausalQueries: Make, Update, and Query Binary Causal Models

make_par_values_stops

Description

helper to remove stops and reduce complexity of make_par_values

Usage

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.

CausalQueries documentation built on June 22, 2024, 6:50 p.m.