R: Plot the Component CDF

compCDF {mixtools} | R Documentation

## Plot the Component CDF

### Description

Plot the components' CDF via the posterior probabilities.

### Usage

    compCDF(data, weights,
            x=seq(min(data, na.rm=TRUE), max(data, na.rm=TRUE), len=250),
            comp=1:NCOL(weights), makeplot=TRUE, ...)

### Arguments

`data` | A matrix containing the raw data. Rows are subjects and columns are repeated measurements.
`weights` | The weights to compute the empirical CDF; however, most of time they are the posterior probabilities.
`x` | The points at which the CDFs are to be evaluated.
`comp` | The mixture components for which CDFs are desired.
`makeplot` | Logical: Should a plot be produced as a side effect?
`...` | Additional arguments (other than `lty` and `type`, which are already used) to be passed directly to `plot` and `lines` functions.

### Details

When `makeplot` is `TRUE`, a line plot is produced of the CDFs evaluated at `x`. The plot is not a step function plot; the points (x, CDF(x)) are simply joined by line segments.

### Value

A matrix with `length(comp)` rows and `length(x)` columns in which each row gives the CDF evaluated at each point of `x`.

### References

McLachlan, G. J. and Peel, D. (2000) Finite Mixture Models, John Wiley \& Sons, Inc.

Elmore, R. T., Hettmansperger, T. P. and Xuan, F. (2004) The Sign Statistic, One-Way Layouts and Mixture Models, Statistical Science 19(4), 579–587.

### See Also

`makemultdata`, `multmixmodel.sel`, `multmixEM`.

### Examples

    ## The sulfur content of the coal seams in Texas

    set.seed(100)

    A <- c(1.51, 1.92, 1.08, 2.04, 2.14, 1.76, 1.17)
    B <- c(1.69, 0.64, .9, 1.41, 1.01, .84, 1.28, 1.59)
    C <- c(1.56, 1.22, 1.32, 1.39, 1.33, 1.54, 1.04, 2.25, 1.49)
    D <- c(1.3, .75, 1.26, .69, .62, .9, 1.2, .32)
    E <- c(.73, .8, .9, 1.24, .82, .72, .57, 1.18, .54, 1.3)

    dis.coal <- makemultdata(A, B, C, D, E,
                             cuts = median(c(A, B, C, D, E)))
    temp <- multmixEM(dis.coal)

    ## Now plot the components' CDF via the posterior probabilities

    compCDF(dis.coal$x, temp$posterior, xlab="Sulfur", ylab="", main="empirical CDFs")

[Package mixtools version 1.2.0 Index]