similar to: uniform generator (default)

There is a bug in AIC.default and AIC.lm, as illustrated below. (I've only checked this under 1.6.1, and can't easily check if it has already been reported since the site is down.) > lm1 <- lm(y ~ x, list(x=1:10, y=jitter(1:10))) > lm2 <- lm(y ~ x, list(x=1:10, y=jitter(1:10))) > AIC(lm1, lm2) df AIC lm1 3 -18.662493 lm2 3 -7.265906 > AIC(lm1, lm2, k = 2)

On 09/19/2018 10:03 AM, Ben Bolker wrote: ... > Balancing backward compatibility and correctness is a tough problem > here. I think improvements in the RNG is a situation where backward compatibility is not really going to be lost, because people can specify the old generator, they just will not get it by default. My opinion is that the default needs to generally be the best option

On 2018-09-19 09:40 AM, David Hugh-Jones wrote: > On Wed, 19 Sep 2018 at 13:43, Duncan Murdoch <murdoch.duncan at gmail.com> > wrote: > >> >> I think the analyses are correct, but I doubt if a change to the default >> is likely to be accepted as it would make it more difficult to reproduce >> older results. > > > I'm a bit alarmed by the logic

I'm running into problems with set.seed--maybe I'm misunderstanding something. I'm running R 1.5.1 on Windows 2000. I'm basically trying to capture the random seed so that I can reproduce a simulation if it's necessary later. Using set.seed, I can certainly get reproducible results, but not the results I get on the first pass. Here's an example: # Generate a random

Hi everyone, is there a function to fit a frechet distribution? The only thing I found is gev.fit from ismev which fits a generalized extreme value distribution (if shape>1 => Frechet) . Is there a function to only fit a frechet? Thank you Benjamin

On 7 February 2015 at 19:52, otoomet wrote: | random numbers. For instance, can I be sure that | set.seed(0); print(runif(1)); print(rnorm(1)) | will always print the same numbers, also in the future version of R? There Yes, pretty much. I've been lurking here over fifteen years, and while I am getting old and forgetful I can remember exactly one such change where behaviour was changed,

Hi, Our department has detected a bug in the implementation of the Kinderman-Ramage generator for normal random variates in version 1.7.0, which can be seen from the below R session. (Consecutive calls for chisq.test(...) always gives p-values very close to 0.) We have already encountered this bug in version 1.6.2 The error is in file R-1.7.0/src/nmath/snorm.c Here is a patch for this file to

Unfortunately, RNGkind is buggy. It will not generate warnings except the full name "Buggy Kinderman-Ramage" is supplied for normal.kind. match.arg is supposed to be called before "==" comparison. ======================================== Shengqiao Li Research Associate The Department of Statistics PO Box 6330 West Virginia University Morgantown, WV 26506-6330

Dear R Helpers This is the R code (which I have slightly changed) I got in VGAM package for estimating the parameters of FRECHET. _________________________________________________________________ y = rfrechet(n <- 100, shape=exp(exp(0))) # (A) fit3 = vglm(y ~ 1, frechet3(ilocation=0), trace=TRUE, maxit=155) # (B) coef(fit3, matrix=TRUE) # (C)

hello everybody i want to use the maximum likelihood method to estimate FRECHET parameters of my sample data. Should it work with fitdistr in the package MASS? I only find how to do it for GEV, Gumbel, and almost all other distributions, but FRECHET? I would be very happy if somebody can tell me how to do fit the FRECHET distribution! Thanks Nadja Riedwyl

I've rolled up R-1.7.1.tgz a short while ago. This is a patch version mainly fixing up an assortment of issues (see below). Note also that it comes with an updated set of recommended packages, fixing a couple of nasty issues in at least foreign and nlme. You can get it from http://cran.us.r-project.org/src/base/R-1.7.1.tgz or wait for it to be mirrored at a CRAN site nearer to you. Binaries

I've rolled up R-1.7.1.tgz a short while ago. This is a patch version mainly fixing up an assortment of issues (see below). Note also that it comes with an updated set of recommended packages, fixing a couple of nasty issues in at least foreign and nlme. You can get it from http://cran.us.r-project.org/src/base/R-1.7.1.tgz or wait for it to be mirrored at a CRAN site nearer to you. Binaries

Dear R Helpers Which package is available for estimatine the parameters of three parameter FRECHET distribution. Also, how to generate the random numbers for Frechet using these three estimated parameters. Thanking in advance Maithili

Dear R helpers I have some data and through some other software, it is understood that I can fit the Frechet Distribution to it. However, I need to fit the distribution using R code only. I have searched many R packages and one R helper has suggested some sites too, but unfortunately parameters couldn't be estimated. Using LMOM package, I know how to estimate the parameters of Generalized

Dear All- I am looking at the bivariate point process model for extreme values as described in Section 8.3.2 of Coles book. I am stuck at a very low level in being unable to reproduce the initial step of transforming the data to unit Frechet margins. In particular, I am unable to reproduce the wave-surge pairs distribution after transformation to Frechet scale (Figure 8.6 of Coles

Hi, is there any package (or source code snippet) that will evaluate the Frechet distance for curves represented as sets of points? Searching around only threw up references to a Frechet distribution. Thanks, ------------------------------------------------------------------- Rajarshi Guha <rxg218 at psu.edu> <http://jijo.cjb.net> GPG Fingerprint: 0CCA 8EE2 2EEB 25E2 AB04 06F7 1BB9

Hi all, I face the following problem. I have two variables x,y. I have also calculated the surface z. When I am drawing the surface with function >levelplot (in library lattice) everything is OK. I have the legend etc ... Then I am trying to plot x,y on the same graph. So I am doing : >points(x,y) But, the points are not in the correct position. They are a little bit shifted to the

I wonder how useful a (set of?) "time machine" functions which look up /infer things like this based on a date would be. Could ease the pain of changes generally, though not remove it completely. ~G On Wed, Aug 31, 2016 at 5:45 PM, Paul Gilbert <pgilbert902 at gmail.com> wrote: > > > On 08/30/2016 06:29 PM, Duncan Murdoch wrote: > >> I don't see evidence of

?kml? is an implementation of k-means for longitudinal data (or trajectories). This algorithm is able to deal with missing value and provides an easy way to re roll the algorithm several times, varying the starting conditions and/or the number of clusters looked for. KmL 1.1.1 addition: - 7 imputations methods for longitudinal data - Calculus of three qualities criterion (Calinski&Harabatz,

?kml? is an implementation of k-means for longitudinal data (or trajectories). This algorithm is able to deal with missing value and provides an easy way to re roll the algorithm several times, varying the starting conditions and/or the number of clusters looked for. KmL 1.1.1 addition: - 7 imputations methods for longitudinal data - Calculus of three qualities criterion (Calinski&Harabatz,