Hi Zeng, I just glanced at the link, but I think this is what you are after:
x=rnorm(1000)#1000 random samples from N(0,1) y=rlnorm(1000)#1000 random samples from Lognormal(0,1) fx=ecdf(x)#Empirical cumulative density function of x fy=ecdf(y)#Empirical cumulative density function of y #Histogram of data hist(x) hist(y) n=seq(-4,30,.1)#Quantiles to be applied to the F(x) plot(fx(n), fy(n))#Probability plot If you are testing data against a known distribution (i.e. Normal) you may want to use the distribution function for that distribution (i.e. pnorm for the Normal distr) instead of the ecdf since that will provide you with an exact answer. i.e. plot(pnorm(n), fy(n)) Now, QQ plots are usually more useful to compare distributions since they are more sensitive to small discrepancies in the data. Take a look at qqplot and qqnorm for examples of how to create qqplots in R I hope this helps. Francisco along zeng wrote: > Hi all, > I am a freshman of R,but I am interested in it! Those days,I am > learning pages on NIST,with url > http://www.itl.nist.gov/div898/handbook/eda/section3/probplot.htm, > I am meeting a problem about probability plot and I don't know how to > plot a data set with R. > Could somebody tell me the answer,and a example is the best! I will > look forward to your answer. > Thank you very much. > > ______________________________________________ > [email protected] 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. > ______________________________________________ [email protected] 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.
