map {mclust} | R Documentation

## Classification given Probabilities

### Description

Converts a matrix in which each row sums to 1 into the nearest matrix of (0,1) indicator variables.

### Usage

    map(z, warn=TRUE, ...)

### Arguments

`z` | A matrix (for example a matrix of conditional probabilities in which each row sums to 1 as produced by the E-step of the EM algorithm).
`warn` | A logical variable indicating whether or not a warning should be issued when there are some columns of `z` for which no row attains a maximum.
`...` | Provided to allow lists with elements other than the arguments can be passed in indirect or list calls with `do.call`.

### Value

A integer vector with one entry for each row of z, in which the i-th value is the column index at which the i-th row of `z` attains a maximum.

### References

C. Fraley and A. E. Raftery (2002a). Model-based clustering, discriminant analysis, and density estimation. Journal of the American Statistical Association 97:611-631.

C. Fraley and A. E. Raftery (2002b). MCLUST:Software for model-based clustering, density estimation and discriminant analysis. Technical Report, Department of Statistics, University of Washington.

See http://www.stat.washington.edu/mclust.

### See Also

`unmap`, `estep`, `em`, `me`

### Examples

    data(iris)
    irisMatrix <- as.matrix(iris[,1:4])
    irisClass <- iris[,5]

    emEst <- me(modelName = "VVV", data = irisMatrix, z = unmap(irisClass))

    map(emEst$z)

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