similar to: potential bug in simulate.lm when gaussian(link != "identity")

Dear R developers, I did not get any reply concerning my email from last week concerning the bug I found in stats::simulate.lm(). The bug shows up when called upon a GLM with family gaussian(). I am confident it is a genuine bug related to a mix-up between weights and prior weights that only impacts the gaussian family (other families have their own simulate functions defined elsewhere). I

Thanks a lot Jiefei, I had thought of defining a binary operator (inspired by pipes) or simply using an additional condition in the if() calls [e.g. if(foo & fn(bar)) doSomeThing; with fn(bar) returning a logical], but both are workaround that I do not find as elegant as a proper control-flow construct. Thus two questions remain: - is it possible to create a control-flow construct in pure R?

Hi all, Could anyone refer to me to a good source to learn how to program a simple control-flow construct* in R, or provide me with a simple example? Control-flow constructs are programmed as primitives, but I would like to be able to do that (if possible) in pure R. The general context is that those functions are a mystery to me. The motivating example is that I would like to create a function

Hi all, not sure if you will call this a bug or something else but the following silly call trigger a low level error: foo <- list(x=1) class(foo) <- "new" print.new <- function(x, ...) print(mget(names(formals()))) foo > Error: C stack usage 7969412 is too close to the limit -- Alexandre Courtiol http://sites.google.com/site/alexandrecourtiol/home *"Science is

Hi Alexandre, I'm not an R expert so this is only my personal thought: I don't think you can achieve what you want exactly. A possible solution would be defining a binary operator %*%, where you can replace the asterisk with any function name you want. The function %*% is special since it has two arguments, left operand and right operand respectively. You then can call the `substitute`

Dear all, I am struggling with an issue related to static vignettes: they work, but only when present in double in the tarball -- in the folder inst/doc and vignettes; see below for details. Details: I am pre-compiling heavy vignettes thanks to the vignette builder R.rsp. So basically, I have PDF files which I want the package to use as Vignettes. For this, I have the following in my

Noted Duncan and TRUE... I cannot do more immediately unfortunately, that is always the issue of asking a last minute panic attack question before teaching a course involving the package... I do have /doc in my .Rbuildignore for reasons I can no longer remember... I will dig and create a MRE/reprex. The students will download heavy packages, but they probably won't notice. *Apologies* In the

Dear Knowledgeable R Community Members, Please excuse my ignorance, I apologize in advance if this is an easy question, but I am a bit stumped and could use a little guidance. I have a finite mixture modeling problem -- for example, a 2-component gaussian mixture -- where the components have a large overlap, and I am trying to use the "mclust" package to solve this problem. I need

Dear R Helpers, I have searched for any R package or code for simulating multivariate fractional Brownian motion (mFBM) or multivariate fractional Gaussian noise (mFGN) when a covariance matrix are given. Unfortunately, I could not find such a package or code. Can you suggest any solution for multivariate FBM and FGN simulation? Thank you for your help. Best Regards, Ryan ----- Wonsang You

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Hi All, I am using em() function to estimate a poisson-gaussian process from a univariate one dimension time series, but not sure how to do. In the help manual, it specify that in "pro" of the argument "parameter", if the model includes a Poisson term for noise, there should be one more mixing proportion than the number of Gaussian components. But in the example, the parameter

Hi All, I am trying to use A Gaussian quadrature over the interval (-infty,infty) with weighting function W(x)=exp(-(x-mu)^2/sigma) to estimate an integral. Is there a way to do it in R? Is there a function already implemented which uses such weighting function. I have been searching in the statmode package and I found the function "gauss.quad(100, kind="hermite")" which uses

Hello, I'm Emanuela, I'm implemented a survival analysis and I'm trying to use a frailty model with inverse gaussian distribution, but I'm not able to find the right code, because it seems to be only a gamma and a gaussian distribution. Is there also the inverse gaussian distribution? Thanks a lot Emanuela Rossi

Hi, As far as I know, there exist some programs via the function INLA, but I'm so curious if there is a specific function directly used to fit the log Gaussian Cox process model and predict the latent Gaussian field. That is, if I have a data points, then I input it in the function and don't need to revise the program. Thanks for your help. Joseph -- View this message in context:

Dear all, I am trying to fit a double gaussian to some data using the mixdist package: --- begin code --- ? library(mixdist) ? time <- seq(673,723) ??counts <- c(3,12,8,12,18,24,39,48,64,88,101,132,198,253,331,419,563,781,1134,1423,1842,2505,374,6099,9343,13009, ? ? ? ? ? ? ? ? ? ?15097,13712,9969,6785,4742,3626,3794,4737,5494,5656,4806,3474,2165,1290,799,431,213,137,66,57,41,35,27,27,27) ?

Hello, I am using the parameterized EM- Algorithm in clustering context. I use generated datasets, containing 5000 points in 20 dimensions with 5 clusters. The following poses a problem for me: emEst<-me(modelName="EEV",data=data[,1:numDimensions],z=unmap(x)) emEst<-me(modelName="VEV",data=data[,1:numDimensions],z=unmap(x)) coordProj(main="Model

Dear colleague, I am interested by tools allowing fitting a gaussian curve (or surface) to a distribution of the kind y = f(x) ( or z = g(x,y).) both Fortran and C languages would be usefull. What kind of routines could you suggest? What are the adresses from which they can be downloaded? with many thanks and best regards, Jean Guibert --

>From what I understand, loess in R uses the standard tri-cube function. SAS/INSIGHT offers loess with Gaussian weights. Is there a function in R that does the same? Also, can anyone offer any references comparing properties between tri-cube and Gaussian weights in LOESS? Thanks. - Andr? -- View this message in context:

Hello everybody, I have encountered a problem with the inverse Gaussian distribution. It is very likely that it will not work regardless of the data input. I have programmed this regression and it works fine no matter which distribution the response comes from. If you run this example (first tried and already got the error) set.seed(1234) y = abs( rnorm(150) ) glm( y ~ ., iris, family =

Hey, Dose R include some package for Gaussian Mixture Model data generation and parameters estimation? Now I want to assign lots of multivariate data into a GMM model. So just wondering if given sample data, can we use some functions to estimate the compoents' density function. Thanks for your support. Fred -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-