search for: suppdists

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 (!r...

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 > > [inverse.gaussian()$simulate] depends (in a loose sense) on SuppDists > > (it...

..., at 16:22, Ben Bolker <bbolker at gmail.com> wrote: >> >> >> >> 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 >>>> [inverse.gaussian()$simulate] depends (in a loose sense) on SuppDists...

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")...

...is. -Bob > On Sep 29, 2019, at 16:22, Ben Bolker <bbolker at gmail.com> wrote: > > > > 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 >>> [inverse.gaussian()$simulate] depends (in a loose sense) on SuppDists >>> (it...

>>>>> 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 > [inverse.gaussian()$simulate] depends (in a loose sense) on SuppDists > (it fails if the SuppDists n...

Hello I am searching ghyper package (generalized hypergeometric distributions). Does anyone can send it to me? Regards from Mexico Lizbeth Román [[alternative HTML version deleted]]

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

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 SuppDists package alone contains distributions which are not implemented in R base. Could...

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 R base package. thanks, Ravi.

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

...please let > me know the command syntax to find the mean of Beta Negative Binomial > Distribution for the following parameters: > > n=3 > alpha=0.5 > beta=3 > > Here is the documenation page for R which mentions this distribution > > http://rweb.stat.umn.edu/R/library/SuppDists/html/ghyper.html > > Using Mathematica, I get (-18) for the mean and -150 for the variance, > and wanted to verify this with R, since there is a negative sign which is > confusing me. > > Mathematica says the formula for the mean is n*beta/(alpha-1) and that > is why the ne...

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 3...

Hello, I need help in performing a Van_der_Waerden normal scores test in R. I have two arrays of scores(final on therapy scores from drug and placebo) and want to use the normal scores procdeure to test for significance. (observations are unequal in number - due to dropouts). Could you please help me out with the coding or let me know if there is a package that can be used (for example,

...apted to R 1.8.0 # version 2.1 adapted to R 1.7.0 # version 2, scaled to get 1 +/- 0.1 sec with R 1.6.2 # using the standard ATLAS library (Rblas.dll) # on a Pentium IV 1.6 Ghz with 1 Gb Ram on Win XP pro # revised and optimized for R v. 1.5.x, 8 June 2002 # Requires additionnal libraries: Matrix, SuppDists # Author : Philippe Grosjean # eMail : phgrosjean at sciviews.org # Web : http://www.sciviews.org # License: GPL 2 or above at your convenience (see: http://www.gnu.org) # # Several tests are adapted from the Splus Benchmark Test V. 2 # by Stephan Steinhaus (stst at informatik.uni-frankfurt.de)...

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

...README for details. URL: http://www.r-project.org Index of Contents (Text) Reference Manual (PDF) Package Sources AnalyzeFMRI CoCoAn Devore5 EMV GLMMGibbs GenKern GeneSOM KernSmooth Matrix NISTnls Oarray PHYLOGR PTAk RArcInfo RMySQL RODBC RPgSQL RandomFields RmSQL Rstreams Rwave SASmixed SuppDists VR XML acepack adapt akima ash bindata blighty boot bootstrap bqtl car cclust cfa chron cluster cmprsk coda conf.design cramer date diamonds dse e1071 ellipse event.chart exactRankTests fastICA fdim fields foreign fracdiff gafit gee geoR gld gregmisc gss ineq leaps lgtdl lmtest locfit logspline lok...

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'...

...ge (4 core, AMD processor, 11.04 64-bit Ubuntu): > source("R-benchmark-25.R") Loading required package: Matrix Loading required package: lattice Attaching package: 'Matrix' The following object(s) are masked from 'package:base': det Loading required package: SuppDists R Benchmark 2.5 =============== Number of times each test is run__________________________: 3 I. Matrix calculation --------------------- Creation, transp., deformation of a 2500x2500 matrix (sec): 1.237 2400x2400 normal distributed random matrix ^1000____ (sec): 0.86133333333...