simGausFromDAG {causalDisco} | R Documentation |
Simulates a jointly Gaussian dataset given a DAG adjacency matrix. The data is simulated using linear structural equations and the parameters (residual standard deviations and regression coefficients) are sampled from chosen intervals.
simGausFromDAG(
amat,
n,
regparLim = c(0.5, 2),
resSDLim = c(0.1, 1),
pnegRegpar = 0.4,
standardize = FALSE
)
amat |
An adjacency matrix. |
n |
The number of observations that should be simulated. |
regparLim |
The interval from which regression parameters are sampled. |
resSDLim |
The interval from which residual standard deviations are sampled. |
pnegRegpar |
The probability of sampling a negative regression parameter. |
standardize |
If |
A variable X_{i}
is simulated as
X_{i} := \sum_{Z \in pa(X_{i})} \beta_{Z} * Z + e_{i}
where pa(X_{i})
are the parents of X_{i}
in the DAG.
The residual, e_{i}
, is drawn from a normal distribution.
A data.frame of identically distributed simulated observations.