TeachingDemos (version 2.3)

vis.boxcox: Interactively visualize Box-Cox transformations

Description

Explore the Box-Cox family of distributions by plotting data transformed and untransformed and interactively choose values for lambda.

Usage

vis.boxcox(lambda = sample(c(-1,-0.5,0,1/3,1/2,1,2), 1),
           hscale=1.5, vscale=1.5, wait=FALSE)

vis.boxcoxu(lambda = sample( c(-1,-0.5,0,1/3,1/2,1,2), 1),
                        y, xlab=deparse(substitute(y)), 
                        hscale=1.5, vscale=1.5, wait=FALSE)

vis.boxcox.old(lambda = sample(c(-1, -0.5, 0, 1/3, 1/2, 1, 2), 1))

vis.boxcoxu.old(lambda = sample(c(-1, -0.5, 0, 1/3, 1/2, 1, 2), 1))

Arguments

lambda

The true value of lambda to use.

y

Optional data to use in the transform.

xlab

Label for x-axis.

hscale

The horizontal scale, passed to tkrplot.

vscale

The vertical scale, passed to tkrplot.

wait

Should R wait for the demo window to close.

Value

• The old versions have no useful return value. If wait is FALSE then they will return an invisible NULL, if wait is TRUE then the return value will be a list with the final value of lamda, the original data, and the transformed y (at the final lamda value).

Details

These functions will generate a sample of data and plot the untrasformed data (left panels) and the transformed data (right panels). Initially the value of lambda is 1 and the 2 sets of plots will be identical. You then adjust the transformation parameter lambda to see how the right panels change. The function vis.boxcox shows the effect of transforming the y-variable in a simple linear regression. The function vis.boxcoxu shows a single variable compared to the normal distribution.

References

GEP Box; DR Cox. An Analysis of Transformations. Journal of the Royal Statitical Society. Series B, Vol. 26, No. 2 (1964) 211-252

See Also

bct, boxcox in package MASS

Examples

if(interactive()) {
vis.boxcoxu()
vis.boxcox()
}