qp.edge.prob {qp}R Documentation

Estimate of the non-rejection rate

Description

Calculates the estimate of the non-rejection rate for a pair of variables, that is, the proportion of conditional independence tests that accept the null hypothesis of zero partial correlation given the q-order conditionals.

Usage

qp.edge.prob(S, N, i=1, j=2, q=0, T=500, significance=0.05, binary=TRUE)

Arguments

S sample variance-covariance matrix
N sample size
i index of one variable
j index of another variable
q partial-correlation order
T number of tests per adjacency
significance significance level of each test
binary flag to switch to the compiled C code

Details

By default binary=TRUE and the compiled and faster C code corresponding to this function will be executed. If binary=FALSE is set, then the R code will be executed.

Author(s)

Robert Castelo and Alberto Roverato

References

Castelo, R. and Roverato, A. (2006). A robust procedure for Gaussian graphical model search from microarray data with p larger than n, J. Mach. Learn. Res., 7:2621-2650

See Also

qp.search, qp.ci.test

Examples

data(jmlr06data)
S <- S.bd5.N20
N <- 20
q <- 6
T <- 100

qp.edge.prob(S,N,i=3,j=4,q,T)

[Package qp version 0.2-1 Index]