R: Cumulative Distribution and Quantiles for a univariate...

cdfMclust {mclust} | R Documentation

## Cumulative Distribution and Quantiles for a univariate Gaussian mixture distribution

### Description

Compute the cumulative density function (cdf) or quantiles from an estimated one-dimensional Gaussian mixture fitted using `densityMclust`.

### Usage

    cdfMclust(object, data, ngrid = 100, ...)
    quantileMclust(object, p, ...)

### Arguments

`object` | a `densityMclust` model object.
`data` | a numeric vector of evaluation points.
`ngrid` | the number of points in a regular grid to be used as evaluation points if no `data` are provided.
`p` | a numeric vector of probabilities.
`...` | further arguments passed to or from other methods.

### Details

The cdf is evaluated at points given by the optional argument `data`. If not provided, a regular grid of length `ngrid` for the evaluation points is used.

The quantiles are computed using interpolating splines on an adaptive finer grid.

### Value

`cdfMclust` returns a list of `x` and `y` values providing, respectively, the evaluation points and the estimated cdf.

`quantileMclust` returns a vector of quantiles.

### Author(s)

Luca Scrucca

### See Also

`densityMclust`, `plot.densityMclust`.

### Examples

    x <- c(rnorm(100), rnorm(100, 3, 2))
    dens <- densityMclust(x)
    summary(dens, parameters = TRUE)
    cdf <- cdfMclust(dens)
    str(cdf)
    q <- quantileMclust(dens, p = c(0.01, 0.1, 0.5, 0.9, 0.99))
    cbind(quantile = q, cdf = cdfMclust(dens, q)$y)
    plot(cdf, type = "l", xlab = "x", ylab = "CDF")
    points(q, cdfMclust(dens, q)$y, pch = 20, col = "red3")

    par(mfrow = c(2,2))
    dens.waiting <- densityMclust(faithful$waiting)
    plot(dens.waiting)
    plot(cdfMclust(dens.waiting), type = "l",
         xlab = dens.waiting$varname, ylab = "CDF")
    dens.eruptions <- densityMclust(faithful$eruptions)
    plot(dens.eruptions)
    plot(cdfMclust(dens.eruptions), type = "l",
         xlab = dens.eruptions$varname, ylab = "CDF")
    par(mfrow = c(1,1))

[Package mclust version 5.4.8 Index]