beta.special: Compute set of intervention effects

In pcalg: Methods for Graphical Models and Causal Inference

Compute set of intervention effects

Description

This function is DEPRECATED! Use ida instead.

Usage

beta.special(dat=NA, x.pos, y.pos, verbose=0, a=0.01, myDAG=NA,
             myplot=FALSE, perfect=FALSE, method="local", collTest=TRUE,
             pcObj=NA, all.dags=NA, u2pd="rand")

Arguments

dat	Data matrix
x.pos, y.pos	integer column positions of x and y in dat.
verbose	0=no comments, 2=detail on estimates
a	Significance level of tests for finding CPDAG
myDAG	Needed if true correlation matrix shall be computed
myplot	Plot estimated graph
perfect	True cor matrix is calculated from myDAG
method	"local" - local (all combinations of parents in regr.); "global" - all DAGs
collTest	True - Exclude orientations of undirected edges that introduce a new collider
pcObj	Fit of PC Algorithm (CPDAG); if this is available, no new fit is done
all.dags	All DAGs in the format of function allDags; if this is available, no new function call allDags is done
u2pd	function for converting a UDAG to a PDAG; "rand": udag2pdag; "relaxed": udag2pdagRelaxed; "retry": udag2pdagSpecial.

Value

estimates of intervention effects

Author(s)

Markus Kalisch ([e-mail])

See Also

pcAlgo, dag2cpdag; beta.special.pcObj for a fast version of beta.special(), using a precomputed pc-object.

pcalg documentation built on May 29, 2024, 5:24 a.m.