boxcox from MASS and bct from TeachingDemos do different things. The boxcox
function does not return the transformed y values, it returns log-likelihood
values for various values of lambda, these values can be used to decide which
value of lambda to use (generally it is used by giving a sequence of lambda
values then looking at the plot (see the plotit argument)).
It is generally not a good idea to just take the lambda with the highest
log-likelihood, rather look for values of lambda within the confidence interval
that make scientific sense.
Once you have decided on a value of lambda to use then you can use the bct
function from TeachingDemos (or other ways) to compute the transformed y values.
Hope this helps,
-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch on behalf of Torsten Mathies
Sent: Sat 7/29/2006 12:52 AM
To: r-help@stat.math.ethz.ch
Subject: [R] boxcox transformation
I''ve got a vector of data (hours to drive from a to b) y.
After a qqplot I know, that they don''t fit the normal probability.
I would like to transform these data with the boxcox transformation
(MASS), that they fit the model.
When I try
ybx<-boxcox(y~1,0)
qqnorm(ybx)
the plot is different from
library (TeachingDemos)
ybct<-bct(y,0) //
qqnorm(ybct)
How can I transform y to fit with the normal probability model?
Yours
Torsten
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