pcSelect_stable {ParallelPC}

Estimate subgraph around a response variable using pcSelect

Description

This is the stable version (order independent version) of the pcSelect function (pc-Simple algorithm) in the pcalg package.

Usage

pcSelect_stable(y, dm, alpha, corMethod = "standard", method = "stable",
  verbose = FALSE, directed = FALSE)

Arguments

y

The target (response) variable.

dm

Data matrix with rows are samples and columns are variables.

alpha

Significance level of individual partial correlation tests.

corMethod

"standard" or "Qn" for standard or robust correlation estimation

method

Character string specifying method; the default, "stable" provides an Order-independent version.

verbose

Logical or in {0,1,2};

FALSE, 0: No output,

TRUE, 1: Little output,

2: Detailed output.

Note that such output makes the function very much slower.

directed

Logical; should the output graph be directed?

Value

G A logical vector indicating which column of dm is associated with y.

zMin The minimal z-values when testing partial correlations between y and each column of dm. The larger the number, the more consistent is the edge with the data.

Examples

##########################################
## Using pcSelect_stable
##########################################
library(pcalg)
library(parallel)
p <- 10
set.seed(101)
myDAG <- randomDAG(p, prob = 0.2)
n <- 1000
d.mat <- rmvDAG(n, myDAG, errDist = "normal")
pcSelect_stable(d.mat[,10],d.mat[,-10], alpha=0.05)