qp.search {qp} | R Documentation |
Calculates the estimates of the non-rejection rates for every pair of variables.
qp.search(S, N, q=0, T=500, significance=0.05, binary=TRUE)
S |
sample variance-covariance matrix |
N |
sample size |
T |
number of tests per adjacency |
q |
partial-correlation order |
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.
A |
matrix with the acceptance test counts |
T |
number of tests per adjacency (copied from the input parameter) |
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
qp.edge.prob
, qp.analyse
, qp.hist
data(jmlr06data) S <- S.bd5.N20 N <- 20 q <- 6 T <- 100 qp.out <- qp.search(S,N,q,T)