You may find the qreference function in the DAAG package helpful. It makes several QQ plots to give a sense of what kind of fluctuations can be expected.
You can also construct a series of any plots you are interested in (using different distributions), and modifying the code in this function may help with this. On Thu, Feb 12, 2009 at 1:04 PM, Jason Rupert <jasonkrup...@yahoo.com> wrote: > By any chance is any one aware of a website, book, paper, etc. or > combinations of those sources that show plots of different distributions? > > After reading a pretty good whitepaper I became aware of the benefit of I the > benefit of doing Q-Q plots and histograms to help assess a distribution. > The whitepaper is called: > "Univariate Analysis and Normality Test Using SAS, Stata, and SPSS*" , (c) > 2002-2008 The Trustees of Indiana University Univariate Analysis and > Normality Test: 1, Hun Myoung Park > > Unfortunately the white paper does not provide an extensive amount of example > distributions plotted using Q-Q plots and histograms, so I am curious if > there is a "portfolio"-type website or other whitepaper shows examples of > various types of distributions. > > It would be helpful to see a bunch of Q-Q plots and their associated > histograms to get an idea of how the distribution looks in comparison against > the Gaussian. > > I think seeing the plot really helps. > > Thank you for any insights. > > > > [[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.
