similar to: ghyper package

I think I should have posted this question here as well. I am posting my question here since it is R related. Please see below. I originally posted this to sci.stat.math "Nasser Abbasi" <nma at 12000.org> wrote in message news:Mm4gj.28843$R92.4987 at newsfe16.phx... > > I think R documentation is a bit hard for me to sort out at this time. > > I was wondering if

Hi. I''m a beginner, but I have a basic puppet setup working. I am doing a manual tarball installation and it seems to be hanging then eventually timing out on just downloading the file: file { "/opt/hadoop-0.20.0.tar.gz": source => "puppet:///hadoop020/hadoop-0.20.0.tar.gz" } I have another module that does the same things and works, my only guess

SuppDists is orphaned on CRAN (and has been since 2013). https://cran.r-project.org/web/checks/check_results_.html Oddly, the simulate method for the inverse.gaussian family [inverse.gaussian()$simulate] depends (in a loose sense) on SuppDists (it fails if the SuppDists namespace is not available: if (!requireNamespace("SuppDists", quietly = TRUE)) stop("need CRAN

On 2019-09-25 3:26 a.m., Martin Maechler wrote: >>>>>> Ben Bolker >>>>>> on Tue, 24 Sep 2019 20:09:55 -0400 writes: > > > SuppDists is orphaned on CRAN (and has been since 2013). > > https://cran.r-project.org/web/checks/check_results_.html > > > Oddly, the simulate method for the inverse.gaussian family > >

Ah, I spoke too soon. I started putting the demo code into a test suite and ran one check with valgrind and ? sure enough ? there's def more issues (a cpl functions) than the overt/easy ones (and, I went back to the check results page and, also sure enough, they're there, too). They look to be fairly straightforward to resolve but it's going to take a bit longer than "this

Dear list, I would like to suggest a small update the ?Distributions man page of the stats package. The current version contains the following line. The CRAN package \pkg{SuppDists} for additional distributions. I think it would be better to put in this man page a link to the CRAN task view on Distributions http://cran.r-project.org/web/views/Distributions.html. It is not true that the

cor.test and SuppDists give me different P-values for the same Spearman's rho. Which is correct, or am I doing something wrong? > x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1) > y <- c( 2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8) > cor.test(x,y,method="spearman") Spearman's rank correlation rho data: x and y S = 48, p-value =

Forgive me if this is the wrong area to ask this question. I'm happy to inquire to a diff list if that's better. From: http://libguestfs.org/ "Downloads For source see the downloads directory. In Fedora or Red Hat Enterprise Linux: sudo yum install libguestfs-tools On Debian/Ubuntu: sudo apt-get install libguestfs-tools Open a disk image: guestfish --ro -i -a disk.img Other

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, I used the commands below to make Hartley's table, but some values are NA. require(SuppDists) trat = seq(2, 15, 1) gl = seq(2, 40, 1) har = matrix(0, nr=length(gl), nc=length(trat)) for(i in 1:length(gl)) for(j in 1:length(trat)) har[i,j] <- qmaxFratio(.95, df=gl[i], k=trat[j]) rownames(har) <- gl colnames(har) <- trat head(har) The output (head): 2

Hello! I am trying with this question again: I would like to test few distributional assumptions for some behavioral response data. There are few theories about true distribution of those data, like: normal, lognormal, gamma, ex-Gaussian (exponential-Gaussian), Wald (inverse Gaussian) etc. The best way would be via qq-plot, to show to students differences. First two are trivial: qqnorm(dat$X)

I have found the "simulate" method (incorporated in some packages) very handy. As far as I can tell the only class for which simulate is actually implemented in base R is lm ... this is actually a little dangerous for a naive user who might be tempted to try simulate(X) where X is a glm fit instead, because it defaults to simulate.lm (since glm inherits from the lm class), and the

Hi All, I've just rebuild the latest R with the Goto BLAS on our new Intel quad core machines. I did a few basic matrix calculations, and I was very impressed by the performance I saw. I wonder if anyone has a more rigorous benchmarking program for R. I downloaded a old R test/benchmarking program (see below), and this didn't work with the current R, and so I wondered if anyone could

Hello, I was trying to fit a Johnson curve by first figuring out the parameter estimates using JohosnFit of a vector by a group ID using the aggregate function. I.E. aggregate(x, by = list(ID), JohnsonFit) where x is the variable I am trying to perform JohnsonFit on. It is a continuous random variable. However, I keep getting the following error: Error in JohnsonFit(x) : Unbounded solution

Hi All: Package TSERIES is stated to depend on MVA. However, there is no MVA package to be found under the list of package sources. Best wishes, ANDREW tseries: Package for time series analysis Package for time series analysis with emphasis on non-linear and non-stationary modelling Version: 0.7-6 Depends: ts, mva, quadprog Date: 2001-08-27 Author: Compiled by Adrian

Dear R-developer (Marsaglia??) The following piece of code from package SuppDist , routine "dist.cc" seems to have a bug ULONG MWC1019(void){ ULONG long t; int i = endQ-1; t = 147669672LL*Q[i] + Q[endQ]; Q[endQ] = (t>>32); if(i>0) return(Q[i--] = t); i = endQ-1; return(Q[0] = t); } in fact , being "i" a local variable that have automatic storage, it is

Dear R-people Does someone have a routine to ngenerate inverse-gaussian random numbers. I am thinking of something similar to rinvgauss, pinvgauss etc. in S-plus. best regards Helgi -- Helgi Tomasson FAX: 354-552-6806 University of Iceland PHONE:354-525-4571 Faculty of Economics and Business Administration

Hi, I am running R version rw2010 on a Windows 2000 desktop. I am invoking R from Java via the JGR JRI tools. My process consists of repeated calls to R in order to create linear models and process the resulting statistics. I find, however, that the process often dies due to memory allocation errors: lm command:

Hi, I need Beta binomial and Beta negative binomial functions but in R there is only SuppDists package which provide this distributions using a limited parameter space of the generalized hypergeometric distribution (dghyper & Co.) which provide a limited parameter space for Beta binomial and Beta negative binomial functions (e.g. alpha + beta <1 in the Beta negative binomial). I've

Dear R-devel, Can anyone give me some hints on how to go about debugging a strange segfault in my randomForest package? Here's the scoop: A user reported segfault when running predict() in the randomForest package. I asked for the data and code. The combination runs fine under WinXPPro, but does give segfault on one of our Linux boxes running R (1.7.0 through R-devel_2004-01-08) on