From: Spencer Graves <spencer.graves_at_pdf.com>

Date: Sun 07 Aug 2005 - 12:31:41 EST

Date: Sun 07 Aug 2005 - 12:31:41 EST

I don't know of an existing R function to do this. However, it should not be too hard, especially if I had only one with the numbers you gave. I'd compute the observed chi-square, then construct a series of 4 nested "for" loops to generate all 5969040 = 22!/(15! 0! 3! 4!) possible outcomes that sum to 22, compute the chi-square for each, and count how many have a chi-square at least as extreme as what you observed. If I wanted a general algorithm, that would take more work.

If you'd like more help than this, PLEASE do read the posting guide! "http://www.R-project.org/posting-guide.html", show us your code and where you got stuck.

spencer graves

Christine Adrion wrote:

> Hello,

*>
**> I have a question concerning the R-function chisq.test.
**>
**> For example, I have some count data which can be categorized as follows
**> class1: 15 observations
**> class2: 0 observations
**> class3: 3 observations
**> class4: 4 observations
**>
**> I would like to test the hypothesis whether the population probabilities are all equal (=> Test for discrete uniform distribution)
**> If you have a small sample size and therefore a sparse (1xr)-table, then assumptions for chisquare-goodness-of-fit test are violated (the numbers expected are less than 5 in more than 75% of the entries.)
**>
**> ####### R-Program: Chisquare-Test :#########
**>
**> mydata <- c(15,0,3,4)
**> chisq.test(mydata, correct=TRUE, rescale.p = TRUE, simulate.p.value = TRUE, B = 2000)
**>
**>
**> As you cannot ignore the small sample size, I use 'simulate.p.value' is 'TRUE' and therefore the p-value is computed by Monte Carlo simulation with 'B' replicates.
**> But is it also the possible to use an EXACT version of a chisquare goodness-of-fit test without a Monte-Carlo-simulation? How can I calculate this in R?
**>
**>
**>
**> Any hint would be appreciated,
**> Regards,
**> Christine Adrion
**> [[alternative HTML version deleted]]
**>
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**> PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
*

-- Spencer Graves, PhD Senior Development Engineer PDF Solutions, Inc. 333 West San Carlos Street Suite 700 San Jose, CA 95110, USA spencer.graves@pdf.com www.pdf.com <http://www.pdf.com> Tel: 408-938-4420 Fax: 408-280-7915 ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.htmlReceived on Sun Aug 07 12:37:37 2005

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