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Simulate Data from DAG

Source: R/simulate_data.R
simulate_data.Rd

Simulates data from an (augmented) DAG, respecting the optional metadata fields form, for functional form of relationships, and distribution, for the distributions of exogenous nodes and residuals.

Usage

simulate_data(
  x,
  beta_default = round(runif(1, min = -0.6, max = 0.6), 2),
  n = 500,
  run = TRUE,
  duplicated = "unique"
)

Arguments

x

An object of class dagitty.

beta_default

Function used to specify missing edge coefficients. Default: runif(1, min = -0.6, max = 0.6)

n

Atomic integer defining the sample size, default: 500

run

Logical, indicating whether or not to run the simulation. Default: TRUE.

duplicated

Atomic character, indicating how to resolve duplicate terms from multiple edges pointing to the same node. Default: "unique". See Details.

Value

If run is TRUE, this function returns a data.frame with an additional attribute called attr( , which = "script") that contains the script for simulating data. If run is FALSE, this function returns the script as character vector.

Details

Data is simulated sequentially, first from exogenous nodes and then from their descendants. If x is an augmented DAG with metadata indicating the functional form of relationships and distribution of exogenous nodes and residuals, this information is used. If this information is absent, nodes and residuals are assumed to be normally distributed, and edges are assumed to be linear, with coefficients samples based on beta_default.

The argument duplicated controls how multiplicative terms are merged across edges pointing to the same outcome node. The default duplicated = "unique" removes terms that are duplicated across edges (i.e., if two edges point to node "O", and both edges specify .5*E, the resulting function will say .5*E. However, if one edge specifies .2*E and the other specifies .3*E, they are not duplicated and will be added. Alternatively, duplicated = "add" just sums terms across all edges pointing into the same outcome node.

See also

get_nodes, get_edges exogenousVariables

Examples

x <- dagitty::dagitty('
dag {
  X [distribution="rbinom(size = 2, prob = .5)"]
  Z [distribution="rexp()"]
  Y [distribution="rnorm()"]

  X -> Y [form="0.5+X"]
  Z -> Y [form="2*Z"]
  A -> X
}
')
txt <- simulate_data(x, n = 5, run = FALSE)
#> ! No valid distribution for data, used rnorm() instead.
df <- simulate_data(x, n = 5, run = TRUE)
#> ! No valid distribution for data, used rnorm() instead.
df_from_txt <- eval(parse(text = txt))