sinDAG: SIN for acyclic directed graphs

In SIN: A SINful Approach to Selection of Gaussian Graphical Markov Models

Description

This function computes the matrix of simultaneous p-values for SIN model selection for acyclic directed graphs (DAGs). SIN assumes that a total ordering of the variables is available (e.g., as a time-order).

Usage

sinDAG(order,S,n,holm=TRUE)

Arguments

order	a list of pairwise different integers amongst 1,…,p where p is the number of variables. This list specifies a total ordering of the variables by the convention that a list element is smaller than succeeding list elements.
S	a covariance or correlation matrix.
n	the sample size.
holm	Boolean variable indicating whether Holm's p-value adjustment should be used (holm=TRUE) or not (holm=FALSE).

Value

A matrix of simultaneous p-values with NA on the diagonal.

References

Drton, M. \& Perlman, M.D. (2004) Model Selection for Gaussian Concentration Graphs. Biometrika 91(3): 591-602.

Drton, M. \& Perlman, M.D. (2008) A SINful Approach to Gaussian Graphical Model Selection. J. Statist. Plann. Inference 138(4): 1179-1200.

See Also

plotDAGpvalues

Examples

data(fowlbones)
p <- dim(fowlbones$corr)[1]
sinDAG(list(1:p),fowlbones$corr,fowlbones$n)
sinDAG(list(1:p),fowlbones$corr,fowlbones$n,holm=FALSE)
sinDAG(list(3,2,1,4,5,6),fowlbones$corr,fowlbones$n)

Example output

              skull length skull breadth   humerus      ulna     femur
skull length            NA     0.0000000 0.0000000 0.4312672 0.6027246
skull breadth    0.0000000            NA 0.0000001 0.6027246 0.6027246
humerus          0.0000000     0.0000001        NA 0.0000000 0.0000238
ulna             0.4312672     0.6027246 0.0000000        NA 0.0000002
femur            0.6027246     0.6027246 0.0000238 0.0000002        NA
tibia            0.5613670     0.4988285 0.6027246 0.0024489 0.0000000
                  tibia
skull length  0.5613670
skull breadth 0.4988285
humerus       0.6027246
ulna          0.0024489
femur         0.0000000
tibia                NA
              skull length skull breadth   humerus      ulna     femur
skull length            NA     0.0000000 0.0000000 0.7015968 0.9999964
skull breadth    0.0000000            NA 0.0000001 0.9686243 0.9987089
humerus          0.0000000     0.0000001        NA 0.0000000 0.0000397
ulna             0.7015968     0.9686243 0.0000000        NA 0.0000003
femur            0.9999964     0.9987089 0.0000397 0.0000003        NA
tibia            0.9156075     0.8221861 0.9788555 0.0045867 0.0000000
                  tibia
skull length  0.9156075
skull breadth 0.8221861
humerus       0.9788555
ulna          0.0045867
femur         0.0000000
tibia                NA
              skull length skull breadth   humerus      ulna     femur
skull length            NA     0.0000000 0.0000000 0.4312672 0.6027246
skull breadth    0.0000000            NA 0.0000000 0.6027246 0.6027246
humerus          0.0000000     0.0000000        NA 0.0000000 0.0000238
ulna             0.4312672     0.6027246 0.0000000        NA 0.0000002
femur            0.6027246     0.6027246 0.0000238 0.0000002        NA
tibia            0.5613670     0.4988285 0.6027246 0.0024489 0.0000000
                  tibia
skull length  0.5613670
skull breadth 0.4988285
humerus       0.6027246
ulna          0.0024489
femur         0.0000000
tibia                NA

SIN documentation built on May 2, 2019, 8:23 a.m.