qp.edge.prob {qp} | R Documentation |
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.
qp.edge.prob(S, N, i=1, j=2, q=0, T=500, significance=0.05, binary=TRUE)
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 |
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.
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., 7:2621-2650
data(jmlr06data) S <- S.bd5.N20 N <- 20 q <- 6 T <- 100 qp.edge.prob(S,N,i=3,j=4,q,T)