search for: rdiehard

Hello, I am having trouble installing the package from CRAN. As the package compiles I get: * installing *source* package ‘RDieHarder’ ... ** package ‘RDieHarder’ successfully unpacked and MD5 sums checked checking for gcc... gcc checking for C compiler default output file name... a.out checking whether the C compiler works... yes checking whether we are cross compiling... no checking for suffix of executables... checking for...

RDieHarder fails its regression tests on x86_64 (aka "amd64") at CRAN (using Debian), and I see the same on Ubuntu 8.10 in 64 bit. No issues on 32bit. One odd thing is that the program behaves well if run via R --no-save < tests/RDieHarder.R but NOT when started using R --slave &l...

I got hold of the 0.0.7 RDieHarder binary package as zip for Windows from CRANextras but don't know how to invoke its main method dieharder() in R with "file_input" as RNG argument - how to specify path to that input file ? the 0.0.7 as opposed to 0.1.0 doesn't seem to have ''inputfile'' arg for...

Classification: UNCLASSIFIED Caveats: NONE Hello, R users, Has anybody written a function for random test based on the length of longest run of same events. I really appreciate your help. Kyong Park Classification: UNCLASSIFIED Caveats: NONE [[alternative HTML version deleted]]

Can someone point me to an implementation of the "runs up and runs down" test, or does such beast exist in R? From web searches the "runs up and runs down" test is commonly used for testing pseudo-random number generators and in simulations. John C. Davis describes its use in geology in his book on geological statistics (2002). Having searched the full site, I can locate only

A while ago I decided to simply download and install every package on CRAN (disk space is cheap these days...). In the process, I kept loose track of which packages generated one or more 'compilation errors' during the install process (machine runs 64-bit Fedora 8, gcc 4.1 etc. etc). Most of the errors seemed to occur in packages I have little need for at present, but as a courtesy, I

Hi, subject more or less says it all. I freely admit to not having bothered to find some of the online papers about method of testing the quality of random number generators -- but in an idle moment I wondered what to expect from something like the following: randa<-runif(1000) randb<-runif(1000) t.test(randa,randb)$p.value var.test(randa,randb)$p.value [repeat ad nauseum] Is the

Hi all, Could anyone point me to one or more examples in the R sources of a C function that is called without knowing in advance what will be the length (say) of the output vector? To make myself clearer, we have a C function that computes probabilities until their sum gets "close enough" to 1. Hence, the number of probabilities is not known in advance. I would like to have an

...1.5.1), mvnormtest (0.1-9), ncdf4 (1.6), ncdf4 (1.6.1), negenes (1.0-1), oposSOM (0.1-4), pcaPP (1.9-46), phenology (3.29), polySegratioMM (0.6-2), pomp (0.41-3), psgp (0.3-1), QCA (1.0-1), QCA3 (0.0-5), quantreg (4.79), Rcmdr (1.8-4), RcppArmadillo (0.3.0.1), RcppArmadillo (0.3.0), RcppDE (0.1.1), RDieHarder (0.1.2), rEMM (1.0-5), reweight (1.2.1), rockchalk (1.5.4), rrBLUP (3.7), rrcovNA (0.4-03), RRF (1.2), RXMCDA (1.4.2), scriptests (1.0-9), sdcMicro (3.1.1), SDMTools (1.1-11), seewave (1.6.3), sem (3.0-0), SGP (0.9-0.0), SkewHyperbolic (0.3-1), SpatialTools (0.3.5), sphet (1.1-12), splus2R (1.1-1...