mutualInfo: Mutual Information
In bioDist: Different distance measures

Description Usage Arguments Details Value Author(s) References See Also Examples

Calculate mutual information via binning

1 2	mutualInfo(x, ...) MIdist(x, ...)

x

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.

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.

An object of class dist which contains the pairwise distances.

Robert Gentleman

H. Joe, Relative Entropy Measures of Multivariate Dependence, JASA, 1989, 157-164.

dist, KLdist.matrix, cor.dist, KLD.matrix

1 2	x <- matrix(rnorm(100), nrow = 5) mutualInfo(x, nbin = 3)

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Copyright M. P. Wand 1997-2009
            1           2           3           4
2 0.220725846                                    
3 0.104410144 0.066556708                        
4 0.073336461 0.009320618 0.301075824            
5 0.139190106 0.038944099 0.077037020 0.049424411