phonTools (version 0.2-2.2)

sdellipse: Standard deviation Ellipse

Description

Draw standard deviation ellipses around a group of observations.

Usage

sdellipse (points, stdev = 1.96, density = .01,  
add = TRUE, show = TRUE, means = NULL, se = FALSE, ...)

Value

A matrix is returned where the first column indicate x-axis ellipse coordinates and the second column indicates y-axis ellipse coordinates.

Arguments

points

A matrix with two columns in which each row is a different observation from a bivariate normal distribution. Optionally, a 2 by 2 covariance matrix may be specified directly in conjunction with the means parameter.

stdev

The number of standard deviations to be enclosed by the ellipse.

density

The spacing between sampling points along the ellipse. A higher number results in a coarser sampling.

add

If TRUE, the ellipse is added to an existing plot. If FALSE, a new plot is created.

show

If FALSE, no ellipse is drawn.

means

A vector of 2 means, one for each dimension. If these are specified, points is assumed to be a covariance matrix rather than a sequence of observations.

se

If TRUE, a standard error (rather than standard deviation) ellipse is plotted.

...

Additional arguments are passed to the internal call of lines() or plot() as appropriate.

Author

Santiago Barreda <[e-mail]>

Details

This function may be used in 2 different ways: 1) To draw standard deviation ellipses around a set of observations (if 'means' is not specified) 2) To draw ellipses and circles on plots (if 'means' is specified).

Examples

## Examples of draws from different bivariate normal distributions
## and standard deviation ellipses drawn to fit them.
#par (mfrow = c(2,2))
#draws = rmvtnorm (n = 1000, k = 2, sigma = .3)
#plot (draws)
#sdellipse (draws, stdev = 3, lwd = 3, col = 2)

#draws = rmvtnorm (n = 1000, k = 2, sigma = -.3)
#plot (draws)
#sdellipse (draws, stdev = 3, lwd = 3, col = 2)

#draws = rmvtnorm (n = 1000, k = 2, sigma = -.7)
#plot (draws)
#sdellipse (draws, stdev = 3, lwd = 3, col = 2)

#draws = rmvtnorm (n = 1000, k = 2, sigma = .7)
#plot (draws)
#sdellipse (draws, stdev = 3, lwd = 3, col = 2)

## alternatively, a covariance matrix may be specified directly. 
#par (mfrow = c(1,1))
#sdellipse (matrix(c(1,.5,.5,1),2,2), means = c(0,0), 
#add = FALSE, stdev = 1)
#sdellipse (matrix(c(1,-.5,-.5,1),2,2), means = c(0,0), 
#add = TRUE, stdev = 1)