similar to: S-Plus RNG (fwd)

Hi, I have a few questions about the RNG in R; apologies if these are dumb questions: 1. It is my understanding that, among the three types of random number generators available in R now, the best one is the Marsaglia Multicarry. Is this correct? 2. How does the best RNG in R compare (in terms of quality) to the RNG in SPlus? (based on Marsaglia's Super Duper)? Does the Super-Duper 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 have applied L'Ecuyer's TESTU01 suite of RNG tests to the RNGs in R. TESTU01 offers three increasingly more stringent suites, called "Small Crush", "Crush" and "Big Crush". If a particular RNG fails Small Crush, there is no need to apply Big Crush. Below I summarize the results: Number of Tests Failed Small Crush Crush Big Crush

I have commited fixes for 0.64.1 for (1) From: Mai Zhou <mai@ms.uky.edu> > .Random.seed <- c(1, 1:2) > .Random.seed [1] 1 1 2 > runif(5) Warning: Wrong length .Random.seed; forgot initial RNGkind? set to Wichmann-Hill[1] 0.02253721 0.84832584 ........ Here the length of the seed was being tested before the kind was picked out, so the length of the previous type was used. (2)

Full_Name: Richard Simard Version: OS: Linux Submission from: (NULL) (132.204.25.139) In the random number generator MARSAGLIA_MULTICARRY, your algorithm is different than the one in the original reference that you give in the R manual: Marsaglia in his post to the mailing list {\it sci.stat.math} on September 29, 1997. The last line in the R program has a ^ while Marsaglia's algorithm has

On r-help Bill Simpson wrote: >Marsaglia's multiply-with-carry generator is very easy to implement--he >has posted some C code to newsgroups--and seems to test out OK. I wonder >if it would make sense to use one of his generators instead. I would like a system where the random number generator can be specified (perhaps in options or a .RandomGenerator variable). Most often everyone

Hi R-Developers, I had a question about the random number generator used in the R StandAlone Math Library. The stand-alone library depends on the unif_rand() function for most simulated values, and this function is provided in the sunif.c file in the relevant directory. At present, this program implements the "Marsaglia-Multicarry" algorithm, which is described throughout the R

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. ---559023410-851401618-1218751024=:15885 Content-Type: TEXT/PLAIN; charset=ISO-8859-1; format=flowed Content-Transfer-Encoding: QUOTED-PRINTABLE I didn't describe the problem clearly. It's about the number of distinct=20 values. So just

Dear Sir/Madam, I am a beginner in R. Here is my questions. 1. Can you give me one test for randomness (a name and descriptive paragraph is sufficient). 2. I have learned a uniform random number generator [e.g. not the algorithms: i)Wichmann-Hill, ii) Marsaglia-Multicarry, iii) Super-Duper (Marsaglia), iv) Mersenne-Twister, v) TAOCP-1997 (Knuth), or vi) TAOCP-2002 (Knuth)] . Is there any other

On 30 August 2016 at 18:29, Duncan Murdoch wrote: | I don't see evidence of a bug. There have been several versions of the | MT; we may be using a different version than you are. Ours is the | 1999/10/28 version; the web page you cite uses one from 2002. | | Perhaps the newer version fixes some problems, and then it would be | worth considering a change. But changing the default RNG

The idea that the Excel solver "has a good reputation for being fast and accurate" does not withstand an examination of the Excel solver's ability to solve the StRD nls test problems. Solver's ability is abysmal. 13 of 27 "answers" have zero accurate digits, and three more have fewer than two accurate digits -- and this is after tuning the solver to get a good

Hi. I have a VM with CentOs6.2 on KVM. I mount an image of the VM when it's not working with guestmount: root at diehard:~# guestmount -a named-centos.img -i tmp vi /etc/shadow insert comment line into the file (esc yy p 0 i # esc :wq!), save changes, unmount the image, turn on the VM, and I cannot login. I cannot login even if I recover the shadow file. root at diehard:~# guestmount

Hi all, As happens from time to time, discussions on this list appear regarding the use of popular spreadsheets for statistical analysis. One such thread (post of mine) is here: http://maths.newcastle.edu.au/~rking/R/help/03a/6326.html While not advocating such use, these discussions have referenced articles that provide independent reviews of these applications and issues of accuracy, etc.

Folks: I thought the following excerpt from Bruce McCullough's post would be a good candidate for the R fortunes package -- except that it's about Excel, not R! So I nominate it... but leave it to others to say whether it's really "qualified" to be nominated. ---- "The idea that the Excel solver "has a good reputation for being fast and accurate" does not

Hi: I was wondering why Marsaglia's new ziggurat method for generating deviates from the standard normal distribution has not been implemented in the R base package. I know that it is available in SuppDists pacakage of Bob Wheeler, as "rziggurat". According my timing tests, it is about 6 to 7 times faster (on a Pentium 2.4 MHz) machine than the default Inversion method used in

Hi again Sam, Sorry for not replying sooner. I have been ignoring everything for a while to work on the AMMP analysis tool and the continuing saga of migrating the legacy AMMP data. Our consultant has written some programs that take a VERY long time to run :( Anyway, I now know Java and a certain amount of JSP. I hope to be able to get around to this soon. It is all a bit hard now with our

My Asterisk 13 IAX2 trunk posted below: type=friend trunk=yes allowcallerid=yes disallow=all allow=alaw allow=ulaw allow=gsm host=my.super.duper.host username=my.super.duper.username secret=my.super.duper.secret context=sip qualify=500 qualifysmoothing=yes requirecalltoken=no trunk=yes jitterbuffer=yes forcejitterbuffer=yes maxjitterbuffer=300 maxjitterinterps=100 resyncthreshold=1500 tos=ef

Hi All. I have R code whose functionality is being replicated within a C+ program. The outputs are to be compared to validate the conversion somewhat - however (as is always the case) I have stuffed my code with random number calls. Random uniform numbers in C+ are being produced using the (Boost) mersenne-twister generators (mt11213b & mt19937) - which is the default type of generator

R 0.64 on windows NT 4.0 Sometimes I got an error message by doing this > .Random.seed <- c(1, 1:2) > .Random.seed [1] 1 1 2 > runif(5) Warning: Wrong length .Random.seed; forgot initial RNGkind? set to Wichmann-Hill[1] 0.02253721 0.84832584 ........ Sometimes I do not get error message: > .Random.seed <- c(1, 1:2) > .Random.seed [1] 1 1 2 > runif(1) [1] 0.5641106 >

I wouldn't trust the C++ generator to be as good if you seed it this way as if you just seeded it once with your phone number (or any other fixed value) and let it run, because it's probably never been tested to be good when run this way. Is it good enough for the way you plan to use it? Maybe. Duncan Murdoch On 30/07/2020 3:05 p.m., Tommy Jones wrote: > Hi, > > I am