similar to: birthday problem (factorial limit)

I'm looking at algorithms for determining coincidences. In educational testing, it is interesting to look at cheating via the birthday problem where I can assess the probability of n students having the same test score in a class of size k. I was writing my own code for the b-day problem until I ran into the qbirthday() function, which has solutions for the overflow problems I kept running

Recent news articles concerning an article from The Lancet with fabricated data indicate that in the sample containing some 900 or so patients, more than 200 had the same birthday. I was curious and tried out the p and q birthday functions but pbirthday could not handle 250 coincidences with n = 1000. The calculation of upper prior to using uniroot produces NaN, upper<-min(n^k/(c^(k-1)),1)

Hi there, I have written a function to calculate factorials as follows: fact <- function(x) { recurse <- x > 1 x[!recurse] <- 1 if( any(recurse) ) { y <- x[recurse] x[recurse] <- y * fact( y - 1 ) } x } I want to be able to do the famous birthday problem, which will involve the computation of 365!, however it shall get cancelled

Hi all, Does anybody know if it is possible to build a fractional factorial design in R? That is, suppose that we want do design an experiment with 3 factors with 2, 3 and 3 levels, respectivly. However we want to consider, let's say, only 6 from all possible level combinations. Does R design such experiment? Thanks in advance, Caio [[alternative HTML version deleted]]

I've looked through the documentation with R-0.64.1 and have been unable to find a high-level function for evaluation of factorials (i.e., n!, not factorial designs). Is there such a function? It is trivial to code, so everyone could write their own, but it also would be worthwhile as a standard tool. I'm guessing I am just overlooking it.

CentOS is 15 years old today! Hear the story from some of our community members at https://blog.centos.org/2019/04/centos15-2/ Do you have your own story? Drop me a note - rbowen at centosproject.org - to tell me about it. -- Rich Bowen - rbowen at redhat.com @CentOSProject // @rbowen 859 351 9166

It was one year ago today that I released a patch to get OpenSSH compiling on Linux. I had no idea just how much trouble releasing that patch would get me into :) Within days I was inundated with patches, improvements and portability enhancements - contributions which have made portable OpenSSH the success it is today. So allow me to thank the current developers and all of you who have

Hello all, Yesterday I moved using the mv command in Redhat 7.2 ext3 file system to move to /tmp my /mnt/win98/"My Pictures" directory to tmp. The command executed normally, and I actually verified that the subdir was created in /tmp and the files were there in /tmp/"My Pictures" I was doing this to temporarily free space on my vfat windows 98 partition. When I went

Sorry if this dupes, didn't seem to post to the list when I emailed it a few hours ago. Regards, Dean Collins Cognation Pty Ltd dean at cognation.net +1-212-203-4357 +61-2-9016-5642 (Sydney in-dial). ________________________________ From: Dean Collins Sent: Thursday, December 06, 2007 2:49 PM To: 'Asterisk Users Mailing List - Non-Commercial Discussion' Subject: "Happy

I am working on a project that requires me to do very large factorial evaluations. On R the built in factorial function and the one I created both are not able to do factorials over 170. The first gives an error and mine return Inf. Is there a way to have R do these larger calculations (the calculator in accessories can do 10000 factorial and Maple can do even larger) -- View this message in

Dear all, Recently I am generating large random samples (10M) and any duplicated numbers are not desired. We tried several RNGs in R and found Wichmann-Hill did not produce duplications. The duplication problem is the interesting birthday problem. If there are M possible numbers, randomly draw N numbers from them, the average number of dupilcations D = N(N-1)/2/M. For Knuth-TAOCP and

I'm a total newbie at using R, and so there probably is a better way to do this. However, I couldn't find one, and so maybe this will help someone. I was calculating log-likelihoods using a multinomial model, and found that for large n, prod(n:1) wouldn't work to calculate factorials (e.g., prod(200:1) = Inf). The below function calculates the natural log of a factorial (e.g.

Dear R friends, I was wondering if there were factorial and modulus functions out there that I've somehow overlooked? -P. -- Peter L. Hurd, Ph.D. phurd at uts.cc.utexas.edu http://www.zo.utexas.edu/research/phurd fax 512.471-3878 Section of Integrative Biology, University of Texas, Austin TX 78712 USA

I get ties in output from runif() when I generate as few as 10^5 variates and get quite a lot when I generate 10^6. Is this expected?? I haven't seen any duplication with rnorm(10^6), but see varying amounts of duplication using rexp(), rbeta() and rgamma(). I would have thought that there'd be enough precision that one wouldn't get ties until generating samples larger than this..

Dear list, perhpas this question is more suitable for R-dev but since I am not really a developer I post it here first. Apparently the following lines do not create any problem in R: library(combinat) r <- 20; b <- 2; sum( sapply(0:r,function(x) nCm(r,x)^(2*b)) ) > 2^64 while in C I obtain an overflow of data even using unsigned long long and with long double I incurr in precision

Sorry for the stupid question, but is there the factorial function in R? I tried to find it using help.search('factorial') but got nothing appropriate. Many thanks, -Serge

Version 1.3.1 (2001-08-31) factorial() is not in R. It is in S-Plus with the definition factorial <- function(n) gamma(n + 1) -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-devel mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe" (in the "body", not

Hi, i need to create a fractional factorial design sufficient to estimate the main effects. The factors may have any number of levels, let's say any number from 2 to 6. I've tried to use the library conf.design , but i cannot figure out how to write the code. For example, what is the code for a design with 5 factors (2x3x3x5x2) and only main effects not confounded? thanks in advance!

Hi I have data from an experiment that used a repeated-measures factorial 2x2 design (i.e. each participant contributed data to both levels of both factors). I need a non-parametric version of the repeated-measures factorial ANOVA to analyse the data. SPSS only has non-parametric tests for one-way ANOVAs but I have been told that the test I need can be implemented using the R software.

To whom it may concern: I am trying a factorial design a system of mine that has two factors. Each factor was set at four different levels, with one replication for each of the combinations. My data is as follows: A B Response 1 600 2.5 0.0257 2 600 2.5 0.0254 3 600 5