On 05/02/2008 3:22 AM, Antje wrote: > Hi there, > > I have two series of data. plotting the density function of both gives me an > idea about the difference of the data. But I would like to quantify the > difference I see. > > a <- rnorm(100) > b <- rnorm(100) > > da <- density(a) > db <- density(b) > > The problem is that da$x and db$x are different and so I have difficulties to > compare them... Is there any way to force the density funtion to produce the > values for the same x-steps?
If you specify n= and from= and to= to be the same, I'd expect that you'd get the same steps. da <- density(a, n=512, from=min(c(a,b)), to=max(c(a,b))) db <- density(b, n=512, from=min(c(a,b)), to=max(c(a,b))) You could also use approxfun or splinefun to convert the density() output into a function that could be evaluated anywhere. > Or is there any other statistical approach I should use for comparing two > density functions? I need to quantify how much the data-series differ > (density > function is rather complex in my case with skew and several maximas, so not > easily to describe as a mathematical function. > Sorry, I'm not that deep into statistics. Any comments / keywords on this is > welcome... There are a lot of measures of the difference between two distributions. Which one to use depends a lot on the intended purpose. Duncan Murdoch ______________________________________________ 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.
