[R] median by geometric mean -- are we missing what's important?

[Keith Jewell]

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.psych at gmail.com> wrote in message 
news:AANLkTinqFQtHodoLw=3romDKSYiNxbWG5tQJqJM0-Vzu at mail.gmail.com...
> On Mon, Jan 17, 2011 at 9:23 AM, Bert Gunter <gunter.berton at 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.jewell at 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" <ehlers at ucalgary.ca> wrote in message
>>> news:4D3468EF.5010601 at 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.agnessi at 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