vis.boxcox | R Documentation |
Explore the Box-Cox family of distributions by plotting data transformed and untransformed and interactively choose values for lambda.
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))
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 |
vscale |
The vertical scale, passed to |
wait |
Should R wait for the demo window to close. |
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.
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).
Greg Snow 538280@gmail.com
GEP Box; DR Cox. An Analysis of Transformations. Journal of the Royal Statitical Society. Series B, Vol. 26, No. 2 (1964) 211-252
bct
, boxcox
in package MASS
if(interactive()) {
vis.boxcoxu()
vis.boxcox()
}
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