bootstrapMI: Calculate bootstrap p-values for mutual information (MI)...
In maigesPack: Functions to handle cDNA microarray data, including several methods of data analysis

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

This function takes a numerical matrix (or two vectors) and calculates bootstrapped (by permutation) p-values to test if the mutual information value is equal to zero. If the first argument is a matrix, the p-values are calculated between all pairs of rows of the matrix.

1	bootstrapMI(x, y=NULL, bRep, ret="p-value")

`x`	numerical matrix or vector to be analysed. If a vector, the argument `y` must be informed.
`y`	numerical vector. Must be informed if `x` is a vector. If `x` is a matrix, this argument is ignored. Defaults to NULL.
`bRep`	number of permutation to be done in the test.
`ret`	character string with the value to return. Must be 'p-value' (default) for the usual p-value or 'max', to return the maximum absolute correlation value obtained by the permutation.

The method implemented in this function is proposed by Butte and Kohane (2000). The MI value is calculated using the function MI.

The result of this function is a square matrix (length equal to the number of rows of x) if x is a matrix or a numerical value if x and y are vectors. The result is the p-values or maximum MI values calculated by permutation tests.

Gustavo H. Esteves <gesteves@vision.ime.usp.br>

Butte, A.J. and Kohane, I.S. Mutual information relevance networks: functional genomic clustering using pairwise entropy measurements. In Pacific Symposium on Biocomputing, 5, 415-426, 2000 (http://psb.stanford.edu/psb-online/proceedings/psb00/)

MI

x <- runif(50, 0, 1)
y <- rbeta(50, 1, 2)
bootstrapMI(x, y, bRep=100)

z <- matrix(rnorm(100, 0, 1), 4, 25)
bootstrapMI(z, bRep=100)

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