[R] [FORGED] qqPlot vs qqcomp

[peter dalgaard]

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 <mohsenhs82 at 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 <mohsenhs82 at 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 <pdalgd at gmail.com> wrote:
> 
> 
> 
> > On 22 Dec 2015, at 07:30 , mohsen hs via R-help <r-help at 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.mes at cbs.dk  Priv: PDalgd at gmail.com
> 
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-- 
Peter Dalgaard, Professor,
Center for Statistics, Copenhagen Business School
Solbjerg Plads 3, 2000 Frederiksberg, Denmark
Phone: (+45)38153501
Office: A 4.23
Email: pd.mes at cbs.dk  Priv: PDalgd at gmail.com