make_data_single: Generate full dataset
In CausalQueries: Make, Update, and Query Binary Causal Models

make_data_single

R Documentation

Generate full dataset

Description

Generate full dataset

Usage

make_data_single(
  model,
  n = 1,
  parameters = NULL,
  param_type = NULL,
  given = NULL,
  w = NULL,
  P = NULL,
  A = NULL
)

Arguments

`model`	A `causal_model`. A model object generated by `make_model`.
`n`	An integer. Number of observations.
`parameters`	A numeric vector. Values of parameters may be specified. By default, parameters is drawn from priors.
`param_type`	A character. String specifying type of parameters to make ("flat", "prior_mean", "posterior_mean", "prior_draw", "posterior_draw", "define). With param_type set to `define` use arguments to be passed to `make_priors`; otherwise `flat` sets equal probabilities on each nodal type in each parameter set; `prior_mean`, `prior_draw`, `posterior_mean`, `posterior_draw` take parameters as the means or as draws from the prior or posterior.
`given`	A string specifying known values on nodes, e.g. "X==1 & Y==1"
`w`	Vector of event probabilities can be provided directly. This is useful for speed for repeated data draws.
`P`	A `matrix`. Parameter matrix that can be used to generate w if w is not provided
`A`	A `matrix`. Ambiguity matrix that can be used to generate w if w is not provided

Value

A data.frame of simulated data.

Examples


model <- make_model("X -> Y")

# Simplest behavior uses by default the parameter vector contained in model
CausalQueries:::make_data_single(model, n = 5)

CausalQueries:::make_data_single(model, n = 5, param_type = "prior_draw")

# Simulate multiple datasets. This is fastest if event probabilities (w) are  provided
w <- get_event_prob(model)
replicate(5, CausalQueries:::make_data_single(model, n = 5, w = w))

CausalQueries documentation built on Oct. 20, 2023, 1:06 a.m.