qp.ci.test {qp} | R Documentation |
Performs a test for conditional independence between variables indexed by i and j given the conditioning set Q
qp.ci.test(S, N, i=1, j=2, Q=c(), binary=TRUE)
S |
sample variance-covariance matrix |
N |
sample size |
i |
index of one variable |
j |
index of another variable |
Q |
conditioning set |
binary |
flag to switch to the compiled C code |
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.
t.value |
the t-statistic value |
p.value |
the p-value on rejecting the null hypothesis of conditional independence |
Robert Castelo and Alberto Roverato
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, accepted
data(jmlr06data) S <- S.bd5.N20 N <- 20 qp.ci.test(S,N,i=3,j=4,Q=c(5,6,7))