R: Indicator Variables given Classification

unmap {mclust} | R Documentation

## Indicator Variables given Classification

### Description

Converts a classification into a matrix of indicator variables.

### Usage

      unmap(classification, groups=NULL, noise=NULL, ...)

### Arguments

`classification` | A numeric or character vector. Typically the distinct entries of this vector would represent a classification of observations in a data set.
`groups` | A numeric or character vector indicating the groups from which `classification` is drawn. If not supplied, the default is to assumed to be the unique entries of classification.
`noise` | A single numeric or character value used to indicate the value of `groups` corresponding to noise.
`...` | Catches unused arguments in indirect or list calls via `do.call`.

### Value

An n by m matrix of (0,1) indicator variables, where n is the length of `classification` and m is the number of unique values or symbols in `classification`. Columns are labeled by the unique values in `classification`, and the `[i,j]`th entry is 1 if `classification[i]` is the jth unique value or symbol in sorted order `classification`. If a `noise` value of symbol is designated, the corresponding indicator variables are relocated to the last column of the matrix.

### See Also

`map`, `estep`, `me`

### Examples

    z <- unmap(iris[,5])
    z[1:5, ]

    emEst <- me(modelName = "VVV", data = iris[,-5], z = z)
    emEst$z[1:5,]

    map(emEst$z)

[Package mclust version 5.4.5 Index]