FLXMCmvcombi {flexmix} | R Documentation

## FlexMix Binary and Gaussian Clustering Driver

### Description

This is a model driver for `flexmix` implementing model-based clustering of a combination of binary and Gaussian data.

### Usage

    FLXMCmvcombi(formula = . ~ .)

### Arguments

`formula` | A formula which is interpreted relative to the formula specified in the call to `flexmix` using `update.formula`. Only the left-hand side (response) of the formula is used. Default is to use the original `flexmix` model formula.

### Details

This model driver can be used to cluster mixed-mode binary and Gaussian data. It checks which columns of a matrix contain only zero and ones, and does the same as `FLXMCmvbinary` for them. For the remaining columns of the data matrix independent Gaussian distributions are used (same as `FLXMCmvnorm` with `diagonal=FALSE`. The same could be obtained by creating a corresponding list of two models for the respective columns, but `FLXMCmvcombi` does a better job in reporting parameters.

### Value

`FLXMCmvcombi` returns an object of class `FLXMC`.

### Author(s)

Friedrich Leisch

### See Also

`flexmix`, `FLXMCmvbinary`, `FLXMCmvnorm`

### Examples

    ## create some artificial data
    x1 <- cbind(rnorm(300),
                sample(0:1, 300, replace=TRUE, prob=c(0.25, 0.75)))
    x2 <- cbind(rnorm(300, mean=2, sd=0.5),
                sample(0:1, 300, replace=TRUE, prob=c(0.75, 0.25)))
    x <- rbind(x1, x2)

    ## fit the model
    f1 <- flexmix(x~1, k=2, model=FLXMCmvcombi())
    ## should be similar to the original parameters
    parameters(f1)
    table(clusters(f1), rep(1:2, c(300,300)))

    ## a column with noise should not hurt too much
    x <- cbind(x, rnorm(600))
    f2 <- flexmix(x~1, k=2, model=FLXMCmvcombi())
    parameters(f2)
    table(clusters(f2), rep(1:2, c(300,300)))

[Package flexmix version 2.2-4 Index]