estimateMode {fabia} | R Documentation

## Estimation of the modes of the rows of a matrix

### Description

`estimateMode`: R implementation of `estimateMode`.

### Usage

    estimateMode(X,maxiter=50,tol=0.001,alpha=0.1,a1=4.0,G1=FALSE)

### Arguments

`X` | matrix of which the modes of the rows are estimated.
`maxiter` | maximal number of iterations; default = 50.
`tol` | tolerance for stopping; default = 0.001.
`alpha` | learning rate; default = 0.1.
`a1` | parameter of the width of the given distribution; default = 4.
`G1` | kind of distribution, `TRUE`: G1, `FALSE`: G2; default = `FALSE`.

### Details

The mode is estimated by contrast functions G1

(1/a_1) * \ln (\cosh (a1*x))

or G2

- (1/a_1)*\exp(-1/2 * x*x)

The estimation is performed by gradient descent initialized by the median.

Implementation in R.

### Value

`u` | the vector of estimated modes.
`xu` | X-u the mode centered data.

### Author(s)

Sepp Hochreiter

### References

A. Hyvaerinen, ‘Fast and Robust Fixed-Point Algorithms for Independent Component Analysis’, IEEE Transactions on Neural Networks 10(3):626-634, 1999.

### See Also

`fabia`, `fabias`, `fabiap`, `fabi`, `fabiasp`, `mfsc`, `nmfdiv`, `nmfeu`, `nmfsc`, `extractPlot`, `extractBic`, `plotBicluster`, `Factorization`, `projFuncPos`, `projFunc`, `estimateMode`, `makeFabiaData`, `makeFabiaDataBlocks`, `makeFabiaDataPos`, `makeFabiaDataBlocksPos`, `matrixImagePlot`, `fabiaDemo`, `fabiaVersion`

### Examples

    #---------------
    # DEMO
    #---------------

    dat <- makeFabiaDataBlocksPos(n = 100,l= 50,p = 10,f1 = 5,f2 = 5,
           of1 = 5,of2 = 10,sd_noise = 2.0,sd_z_noise = 0.2,mean_z = 2.0,
           sd_z = 1.0,sd_l_noise = 0.2,mean_l = 3.0,sd_l = 1.0)

    X <- dat[[1]]

    # modes <- estimateMode(X)

    # modes$u - apply(X, 1, median)

[Package fabia version 2.33.3 Index]