gen.netglm | R Documentation |
Generates data based on a (generalized) linear network model, where the dependent variable can be either continuous or dichotomous. All the independent variables are dichotomous.
gen.netglm(
n,
m,
family = "gaussian",
intercept = FALSE,
beta = NULL,
red.var = NULL,
seed = NULL,
...
)
n |
The size of the vertex set (|V(G)|) for the random graphs. |
m |
The number of graphs to generate. |
family |
Family of the generalized linear model used to generate the data. The available families are "gaussian" and "binomial". |
intercept |
Logical; should the intercept be simulated?
|
beta |
Values of the true coefficients used to generate the data. If
|
red.var |
Value of the residual variance used when the family is "gaussian". If not provided, the residual variance is set to 1. |
seed |
Integer used as the seed in the generation process. Allows the user to generate the same data consistently. |
... |
other arguments passed on to the function |
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