mclust (version 6.0.1)

unmap: Indicator Variables given Classification

Description

Converts a classification into a matrix of indicator variables.

Usage

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

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.

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.

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)