Dear Saji Ren, Dieter Menne has already pointed out that you lost the negative values in the transformation. Another point is that since you selected the transformation based on the "started" data c888.dl.ma080 + 1200, then you should transform c888.dl.ma080 + 1200 and not c888.dl.ma080. But as Dieter also pointed out, the 0.95 power isn't going to change the distribution of the data much. As well, the problem here is that the distribution is more heavy-tailed than asymmetric, and a Box-Cox transformation isn't going to help.
Regards, John -------------------------------- John Fox Senator William McMaster Professor of Social Statistics Department of Sociology McMaster University Hamilton, Ontario, Canada web: socserv.mcmaster.ca/jfox > -----Original Message----- > From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org] On > Behalf Of Saji Ren > Sent: January-11-10 12:09 AM > To: r-help@r-project.org > Subject: [R] Problem about Box-Cox transformation (topic in html form) > > > Hi: > > 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. > below is the qq-plot of the original data > http://n4.nabble.com/file/n1011015/start%2Bvalue%2Bproblem%2B02.jpeg > Note that the min of my data is -1099, so I add a fix value 1200 to the > original sample. > > I choose the "box.cox.powers" function in package 'car'. Here is the result: > > box.cox.powers(na.exclude(c888.dl.ma080+1200)) > Box-Cox Transformation to Normality > > Est.Power Std.Err. Wald(Power=0) Wald(Power=1) > 0.9526 0.0237 40.2638 -2.0036 > > L.R. test, power = 0: 2014.192 df = 1 p = 0 > L.R. test, power = 1: 3.9807 df = 1 p = 0.046 > > 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. > > Can anyone explain that to me? > > Thank you in advanced. > > > ----- > ------------------------------------------------------------------ > Saji Ren > from Shanghai China > GoldenHeart Investment Group > ------------------------------------------------------------------ > -- > View this message in context: http://n4.nabble.com/Problem-about-Box-Cox- > transformation-topic-in-html-form-tp1011015p1011015.html > Sent from the R help mailing list archive at Nabble.com. > > [[alternative HTML version deleted]] > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
