cov.sel.high.sim: Simulate Example Data for CovSelHigh

In CovSelHigh: Model-Free Covariate Selection in High Dimensions

Description

Function used internally by cov.sel.high to simulates example data used in Häggström (2016).

Usage

cov.sel.high.sim(N, Setting, rep, Models)
	

Arguments

N	The number of observations to be simulated.
Setting	The simulation setting to be used. Unconfoundedness holds given X if Setting=1. M-bias given X if Setting=2.
rep	The number of replications to be simulated.
Models	The type of outcome models to be used, options are "Linear", "Nonlinear" and "Binary".

Value

cov.sel.high returns a list with the following content:

dat	A data frame with simulated data.

Note

cov.sel.high.sim calls the functions rmvbin and mvrnorm.

Author(s)

Jenny Häggström, <[e-mail]>

References

Häggström, J. (2017). Data-Driven Confounder Selection via Markov and Bayesian Networks. ArXiv e-prints.

CovSelHigh documentation built on May 2, 2019, 3:25 a.m.