| Do.sim.matrix.Pearson {NetPreProc} | R Documentation |
Construction of the Pearson correlation matrix
Description
Function to obtain the Pearson correlation matrix between rows of a given matrix.
Usage
Do.sim.matrix.Pearson(M, cut = TRUE, remove.negatives = TRUE, min.thresh = 0)
Arguments
M |
input matrix |
cut |
if TRUE (def.) at least one edge is maintained for each node, all the other edges are set to 0. If false no edgeis set to 0. |
remove.negatives |
if TRUE (def) negative values are replaced with 0 in the correlation matrix |
min.thresh |
minimum allowed threshold (def. 0). If a threshold lower than min.thresh is selected, thanit is substituted by min.thresh. Warning: setting min.thresh to large values may lead to highly disconneted network |
Details
You can also "sparsify" the matrix, by putting to 0 all the weights, by setting a threshold such that at least one edge is maintained for each node. The diagonal values are set to 0.
Value
a square symmetric matrix of the Pearson correlation coefficients computed between the rows of M
Examples
# a gaussian random matrix
D <- matrix(rnorm(20000),nrow=200);
W <- Do.sim.matrix.Pearson (D);
# the same without default parameters
W2 <- Do.sim.matrix.Pearson (D, cut=FALSE, remove.negatives=FALSE, min.thresh=-20);