Yes, of course. I think all the posts up to Bert's addressed the coding question as asked - how to calculate a particular version of the median (not the mean) rather than any underlying, unstated, statistical or scientific question.
IIRC there hasn't been any indication that non-positive values do occur in the OPs environment, so the extension to zero and negatives was (at least for me) an R programming diversion, I was interested in robust answers to the coding question as asked. I'd caution against any assumption that anything I presented was applicable in any particular circumstances! Best regards, Keith J "Joshua Wiley" <jwiley.ps...@gmail.com> wrote in message news:AANLkTinqFQtHodoLw=3romdksyinxbwg5tqjqjm0-...@mail.gmail.com... > On Mon, Jan 17, 2011 at 9:23 AM, Bert Gunter <gunter.ber...@gene.com> > wrote: >> Folks: >> >> I know this may be overreaching, but are we missing what's important? >> WHY do the zeros occur? Are they values less then a known or unknown >> LOD? -- and/or is there positive mass on zero? In either case, using >> logs to calculate a geometric mean may not make sense. Paraphrasing > > Isn't this a bit of a general problem with the geometric mean if there > are 0s or an odd number of negative numbers it becomes 0 or imaginary > (please do correct me if I'm wrong)? > > sqrt(prod(c(2, 0, 54))) > sqrt(prod(c(-2, 2))) > > >> Greg Snow, what is the scientific question? What is the model? >> >> Cheers, >> Bert >> >> >> >> On Mon, Jan 17, 2011 at 9:13 AM, Keith Jewell <k.jew...@campden.co.uk> >> wrote: >>> Just in case some of x are negative (the desired median still exists, as >>> long as the two middle values are non -ve), how about: >>> >>> x <- runif(20, -1, 100) >>> exp(median(log(pmax(0,x)))) >>> >>> It'll give -Inf if the two middle values are negative, when I guess we >>> should get NaN, but I can't see a 1-line way to handle that! >>> >>> Keith J >>> >>> "Peter Ehlers" <ehl...@ucalgary.ca> wrote in message >>> news:4d3468ef.5010...@ucalgary.ca... >>>> I've been reminded by Prof. Brian Ripley that R's >>>> log() function will indeed handle zeros appropriately. >>>> >>>> Apologies to S Ellison and Hadley Wickham. >>>> >>>> Peter Ehlers >>>> >>>> On 2011-01-17 06:55, Peter Ehlers wrote: >>>>> On 2011-01-17 02:19, S Ellison wrote: >>>>>> Will this do? >>>>>> >>>>>> x<- runif(20, 1, 100) >>>>>> >>>>>> exp( median( log( x) ) ) >>>>>> >>>>>> S Ellison >>>>>> >>>>>> >>>>> That's what Hadley proposed, too. It's fine for >>>>> your example, but there is potentially a small >>>>> problem with this method: the data must be positive. >>>>> Since it's not unusual to see data with some zeros, >>>>> the log() would fail. >>>>> >>>>> Depending on what type of data I was going to use >>>>> this modification of the median for, I would consider >>>>> modifying the (quite short) median.default function, >>>>> with appropriate additional data checks. >>>>> >>>>> Peter Ehlers >>>>> >>>>>> >>>>>>>>> Skull Crossbones<witch.of.agne...@gmail.com> 15/01/2011 16:26>>> >>>>>> Hi All, >>>>>> >>>>>> I need to calculate the median for even number of data points.However >>>>>> instead of calculating >>>>>> the arithmetic mean of the two middle values,I need to calculate >>>>>> their >>>>>> geometric mean. >>>>>> >>>>>> Though I can code this in R, possibly in a few lines, but wondering >>>>>> if >>>>>> there >>>>>> is >>>>>> already some built in function. >>>>>> >>>>>> Can somebody give a hint? >>>>>> >>>>>> Thanks in advance ______________________________________________ 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.
