similar to: Difference between "SVN trunk" and "low-memory branch"

>>>>> Henric Winell <nilsson.henric at gmail.com> >>>>> on Tue, 7 Feb 2017 13:37:42 +0100 writes: > Hi, On 2017-02-07 13:12, Benjamin Tyner wrote: >> Hello >> >> When loading a package, I'm wondering if it's frowned >> upon for the package to alter the state of the random >> number

Hello, Inline. Em 12-04-2017 16:40, Henric Winell escreveu: > (Let's keep the discussion on-list -- I've added back R-devel.) > > On 2017-04-12 16:39, Ulrich Windl wrote: > >>>>> Henric Winell <nilsson.henric at gmail.com> schrieb am 12.04.2017 >>>>> um 15:35 in >> Nachricht <b66fe849-bb8d-f00d-87e5-553f866d57e0 at gmail.com>:

Dear all, I'm analyzing a binary outcome using glm() with a binomial distribution and a logit link, and have now reached the point where I'd like to do some model checking. Since my data are in binary form I'd like to collapse over the cross-classification of the factors before the model checking. Are there any nice and simple ways doing this? If so, how? If not, I'd be

Thank you for your help! I gave you an example, you could run it in R . Maybe you will understand my meaning clearly. x <- data.frame(main.name="AAA", x.name=rep(c("Apply","Watermelon","Lemon","Banana",

Dear all, I'm a fairly new R user having two questions regarding gam: 1. The prediction example on p. 38 in the mgcv manual. In order to get predictions based on the original data set, by leaving out the 'newdata' argument ("newd" in the example), I get an error message "Warning message: the condition has length > 1 and only the first element will be used in: if

Hi, I've noted that not all `predict' methods are hidden in the namespace: > methods("predict") [1] predict.ar* predict.Arima* [3] predict.arima0* predict.glm [5] predict.HoltWinters* predict.lm [7] predict.loess* predict.mlm [9] predict.nls* predict.poly [11] predict.ppr* predict.prcomp* [13]

Dear list, I've noticed that influence.measures and cooks.distance gives different results for non-gaussian GLMs. For example, using R-1.9.0 alpha (2003-03-17) under Windows: > ## Dobson (1990) Page 93: Randomized Controlled Trial : > counts <- c(18,17,15,20,10,20,25,13,12) > outcome <- gl(3,1,9) > treatment <- gl(3,3) > glm.D93 <- glm(counts ~ outcome +

Marius Hofert-4------------------------------ > Den 2015-10-09 kl. 12:14, skrev Martin Maechler: > I think so: the code above doesn't seem to do the right thing. Consider > the following example: > > > x <- c(1, 1, 2, 3) > > rank2(x, ties.method = "last") > [1] 1 2 4 3 > > That doesn't look right to me -- I had expected > > >

Hi everyone, I've tried the below on R 1.9.1 and the 2004-08-30 builds of R 1.9.1 Patched and R 2.0.0 on Windows 2000, and the results are consistent. > seq(0.5, 0, by = -0.1) [1] 0.5 0.4 0.3 0.2 0.1 0.0 > seq(0.7, 0, by = -0.1) [1] 7.000000e-01 6.000000e-01 5.000000e-01 4.000000e-01 3.000000e-01 2.000000e-01 1.000000e-01 -1.110223e-16 Is this really the intended behaviour?

Dear all, I've now spent a couple of days trying to learn R and, in particular, the gam() function, and I now have a few questions and reflections regarding the latter. Maybe these things are implemented in some way that I'm not yet aware of or have perhaps been decided by the R community to not be what's wanted. Of course, my lack of complete theoretical understanding of what

Dear Sir I am a university student doing my dissertation, my project is about secure voice in GSM, and I use speex for speech compression. My problem is I am not able to compile the TI CCS project which I downloaded from the official website. I have followed the instruction to modify the directory in .pjt, but I still get error. I tried both Debug and Release mode neither works. the

Dear all, After having set par(mfrow = c(2, 2)) and switching between plot() and xyplot() using R 2.0.0 Patched (2004-10-13) under Windows 2000, the lattice plot gets overplotted. I also tried this under 1.9.1 Patched (2004-09-22), since this is the only older version I've got installed, and it did the same thing apart from that the overplotting now starts in the opposite lower corner.

Full_Name: Henric Nilsson Version: 2.3.0 Patched (2006-05-09 r38014) OS: Windows 2000 SP4 Submission from: (NULL) (83.253.9.137) When supplying an unavailable link to `quasibinomial', the error message looks strange. E.g. > quasibinomial("x") Error in quasibinomial("x") : 'x' link not available for quasibinomial family, available links are "logit",

Dear all, I've got some questions, probably due to misunderstandings on my behalf, related to fitting overdispersed binomial data using glm(). 1. I can't seem to get the correct p-values from anova.glm() for the F-tests when supplying the dispersion argument and having fitted the model using family=quasibinomial. Actually the p-values for the F-tests seems identical to the p-values for

Hi, The added support for semi-transparent colours in `windows' under R-2.6.0 for Windows is much appreciated. However, I've discovered that issuing a `layout' (or `par' with arguments `mfcol'/`mfrow') call and then trying to plot several figures with semi-transparent colour on the same page results in only the first one being fully drawn. E.g. > x <-

------------------ >>>>> Henric Winell <[hidden email]> >>>>> on Wed, 21 Oct 2015 13:43:02 +0200 writes: > Den 2015-10-21 kl. 07:24, skrev Suharto Anggono Suharto Anggono via R-devel: >> Marius Hofert-4------------------------------ >>> Den 2015-10-09 kl. 12:14, skrev Martin Maechler: >>> I think so: the code above

Hi, I've implemented parallelization in one of my packages using the 'parallel' package -- many thanks for providing it! In my package I'm importing 'parallel' and so added it to the DESCRIPTION file's 'Import:' tag and also added a 'importFrom("parallel", ...)' statement in the NAMESPACE file. Parallelization works nicely, but my package

Hey all, I volunteered to put together a proposal regard complex in LLVM. Consider the following to be a strawman meant to spark discussion. It's based on real-world experience with complex but is not expected to cover all use-cases. Proposal to Support Complex Operations in LLVM ---------------------------------------------- Abstract Several vendors and individuals have proposed

Hi! I want to know if a given element <- ('c64') is part of a vector<- ('c64', 'amiga', 'atari'). Does a function exist for this which gives back a logical value? thankx db

Ahead of the Wednesday’s roundtable at the developers’ conference, here is version three of the proposal for first-class complex types in LLVM. I was not able to add Krzysztof Parzyszek’s suggestion of a “cunzip” intrinsic returning two vectors as I could not find examples of intrinsics that return two values at the IR level. The Hexagon intrinsics declared to return two values do not actually