R: Draw Two-Dimensional Ellipse Based on Mean and Covariance

ellipse {mixtools} | R Documentation

## Draw Two-Dimensional Ellipse Based on Mean and Covariance

### Description

Draw a two-dimensional ellipse that traces a bivariate normal density contour for a given mean vector, covariance matrix, and probability content.

### Usage

    ellipse(mu, sigma, alpha = .05, npoints = 250, newplot = FALSE,
            draw = TRUE, ...)

### Arguments

`mu` | A 2-vector giving the mean.
`sigma` | A 2x2 matrix giving the covariance matrix.
`alpha` | Probability to be excluded from the ellipse. The default value is alpha = .05, which results in a 95% ellipse.
`npoints` | Number of points comprising the border of the ellipse.
`newplot` | If newplot = TRUE and draw = TRUE, plot the ellipse on a new plot. If newplot = FALSE and draw = TRUE, add the ellipse to an existing plot.
`draw` | If TRUE, draw the ellipse.
`...` | Graphical parameters passed to `lines` or `plot` command.

### Value

`ellipse` returns an `npoints`x2 matrix of the points forming the border of the ellipse.

### References

Johnson, R. A. and Wichern, D. W. (2002) Applied Multivariate Statistical Analysis, Fifth Edition, Prentice Hall.

### See Also

`regcr`

### Examples

    ## Produce a 95% ellipse with the specified mean and covariance structure.

    mu <- c(1, 3)
    sigma <- matrix(c(1, .3, .3, 1.5), 2, 2)

    ellipse(mu, sigma, npoints = 200, newplot = TRUE)

[Package mixtools version 1.2.0 Index]