R: Parallel Mutual Information Estimation

knnmi {parmigene} | R Documentation

## Parallel Mutual Information Estimation

### Description

A function to perform a parallel estimation of the mutual information of vectors `x` and `y` using entropy estimates from K-nearest neighbor distances.

### Usage

    knnmi(x, y, k=3, noise=1e-12)

### Arguments

`x` | a numeric vector.
`y` | a numeric vector with the same length of `x`.
`k` | the number of nearest neighbors to be considered to estimate the mutual information. Must be less than the number of elements of `x`.
`noise` | the magnitude of the random noise added to break ties.

### Details

The function adds a small random noise to the data in order to break ties due to limited numerical precision.

By default, the function uses all available cores. You can set the actual number of threads used to N by exporting the environment variable `OMP_NUM_THREADS=N`.

### References

Kraskov, Alexander and Stogbauer, Harald and Grassberger, Peter. Estimating mutual information. Phys. Rev. E, 2004.

### See Also

`knnmi.cross`

`knnmi.all`

### Examples

    x <- rnorm(100)
    y <- rnorm(100)
    knnmi(x, y, 5)

[Package parmigene version 1.0.2 Index]