Saji Ren wrote:
>
>
> Recently, I want to perform a transformation on my data to make it more
> normal, meanwhile the order statistics is unchanged. So I decided to use a
> box-cox transformation.
> ...
> Then I compared the result with original data, and it really confused me:
> http://n4.nabble.com/file/n1011015/start%2Bvalue%2Bproblem.jpeg
> The left is my original data sample, you can see that it is symetric and
> the mean is close to 0. It just that the spread is large (there are
> outliers).
> The right is the transformed data, and the distribution is obviously no
> normal.
>
>
This has nothing to do with box.cox.powers.
summary(rnorm(100,0,200)^0.95)
gives about 50 NA from the negative numbers which are not plotted in hist(),
and only the positive are plotted, so you get the skewed distribution.
As an aside, a transformation of 0.95 is rarely worth the pain of having to
explain it to your audience later, even if it is "significant".
Try
library(fortunes)
fortune(234) # Hi Peter, fortunes needs a "search"
Please do not use HTML mail.
Dieter
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