an n by p matrix or ExpressionSet; if x is an ExpressionSet, then the function uses its 'exprs' slot.
...
arguments passed to mutualInfo and MIdist:
nbinnumber of bins to calculate discrete probabilities; default
is 10.
diagif TRUE, then the diagonal of the distance matrix will be
displayed; default is FALSE.
upperif TRUE, then the upper triangle of the distance matrix
will be displayed; default is FALSE.
samplefor ExpressionSet methods, if TRUE, then distances are
computed between samples, otherwise, between genes.
Value
An object of class dist which contains the pairwise distances.
Details
For mutualInfo each row of x is divided into
nbin groups and then the mutual information is computed, treating
the data as if they were discrete.
For MIdist we use the transformation proposed by Joe (1989),
$delta* = (1 - exp(-2 delta))^.5$
where $delta$ is the mutual information. The MIdist is
then $1-delta*$. Joe argues that this measure is then
similar to Kendall's tau, tau.dist.
References
H. Joe, Relative Entropy Measures of Multivariate Dependence,
JASA, 1989, 157-164.