Two ideas: a: Take log of your data and compare with normal distr.
b: Use log="xy" as a graphical parameter. Otherwise, you're on your own. -pd > On 24 Dec 2015, at 10:03 , mohsen hs <mohsenh...@yahoo.com> wrote: > > Hi Peter, > > Thanks once again for your kind reply. > > One quick question, could you please guide me and let me know how I can get > the similar qq plot(log-log scale) that I get from qqcomp, from > qqPlotCensored function(It is similar to qqPlot, and available in EnvStats > http://www.inside-r.org/node/218933 ). > > Thanks a lot. > > Cheers > Mohsen > > > > MHS > > > On Wednesday, December 23, 2015 6:52 PM, mohsen hs <mohsenh...@yahoo.com> > wrote: > > > Hi Peter and Rolf > > Thank you for your time and replying me. It makes sense now. I sincerely > appreciate that. > > Cheers > Mohsen > > > > > On Tuesday, December 22, 2015 10:08 PM, peter dalgaard <pda...@gmail.com> > wrote: > > > > > On 22 Dec 2015, at 07:30 , mohsen hs via R-help <r-help@r-project.org> > > wrote: > > > > The above command gives me a differentplot. I am not sure what part I am > > doing wrong. I appreciate your time forconsidering my request and your > > feedback is highly appreciated. Please find the plots attached. The right > > one is from qqcomp and the left one is from qqPlot. Titles might be > > incorrect. > > They never arrived, but your data weren't actually needed. The crucial > missing information was the packages used. This will do: > > > library(EnvStats); library(fitdistrplus) > > serving <- exp(rnorm(100)) > > qqPlot ( serving, dist ="lnorm", estimate.params = TRUE, add.line = TRUE) > > > > > fitln <- fitdist(serving,"lnorm",method="mle") > > qqcomp(fitln) > > > The difference is quite clearly that qqPlot is doing a QQ-plot of > log(serving) vs. normal quantiles, whereas qqcomp plots serving itself > against lognormal quantiles. So the former is pretty much equal to the latter > on a log-log scale. > > -- > Peter Dalgaard, Professor, > Center for Statistics, Copenhagen Business School > Solbjerg Plads 3, 2000 Frederiksberg, Denmark > Phone: (+45)38153501 > Office: A 4.23 > Email: pd....@cbs.dk Priv: pda...@gmail.com > > > > > > > > > > > > > -- Peter Dalgaard, Professor, Center for Statistics, Copenhagen Business School Solbjerg Plads 3, 2000 Frederiksberg, Denmark Phone: (+45)38153501 Office: A 4.23 Email: pd....@cbs.dk Priv: pda...@gmail.com ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see 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.
