similar to: documentation to upgrade R-package from 32 to 64bit

Dear all, In my attempt to run the below modelling command in R 2.7.0 under windows XP (4GB RAM with /3GB switch set) I receive the following error: Error: cannot allocate vector of size 1.5 Gb I have searched a bit and have tried adding: --max-mem-size=3071M to the command line (when set to 3G I get the error that 3072M is too much) I also run: > memory.size() [1] 11.26125 >

Hello, After much tinkering I managed to build packages using the 64bit version of R with the help of hints from http://www.murdoch-sutherland.com/Rtools/ and http://www.stats.ox.ac.uk/~ripley/Win64/W64porting.html and R-admin Manual. But a hack was required, and this seems to be related to a comment about underscores at the end of the second reference above (but this comment is about FUTURE

Dear all, I am using gamlss (Package gamlss version 4.0-0, R version 2.10.1, Windows XP Service Pack 3 on a HP EliteBook) to relate bird counts to habit variables. However, most models fail because “the global deviance is increasing” and I am not sure what causes this behaviour. The dataset consists of counts of birds (duck) and 5 habit variables measured in the field (n= 182). The dependent

Dear all I am trying to build a package in Windows. I use the following command (which it used to work with previous versions ) and I am getting the following error #-------------------------------------------------------------------------------------------------------------- C:\PROGRA~1\R\rw2000\bin>Rcmd build --binary --use-zip C:\PROGRA~1\R\rw2000\src\library\gamlss * checking for

Hi, I'm a bit puzzled by the gamlss fitting of exponential and lognormal data. Gamlss seems to think that exponentially distributed data fits better with a lognormal distribution, and vice versa. For example, X <- rexp(1000) Gexp <- gamlss(X~1,family=EXP) # X~1 is X tilde 1 GAMLSS-RS iteration 1: Global Deviance = 2037.825 GAMLSS-RS iteration 2: Global Deviance = 2037.825 Glno

Dear all I am trying to create a package in R 1.9.0 and I a getting an error message which I do not understand. (I am using R in Windows XP and 2000) For example the following works well in 1.8.1 C:\Program Files\R\rw1081\src\gnuwin32>make pkg-gamlss ---------- Making package gamlss ------------ adding build stamp to DESCRIPTION installing inst files installing indices not zipping

Hola a tod en s, tengo una duda que la comunidad R me puede ayudar. Estoy trabajando con gamlss, porque tengo una variable respuesta con valores entre 0 y 1 e incluidos estos. La distribución que utilizo com gamlss para este caso es "beta inflated" (Stasinopulos and Rigby 2007. Journal of Statistical Software 23(7)). El modelo que intento correr es: m1<-gamlss(Teleosteos ~

Hello all: Please help me with this "can't find object" issue. I'm trying to get leave-one-out predicted values for Beta-binomial regression. It may be the gamlss issue because the code seems to work when %do% is used. I have searched for similar issues, but haven't managed to figure it out. This is on Windows 10 platform. Thanks in advance, Nik #

Dear all I am using NAMESPACE in my package but I would like the user to be able to overwrite four functions: own.linkfun, own.linkinv, own.mu.eta and own.valideta. These are used to defined "own" link functions. Is there any way of doing that without getting the when I am checking the package? This is what I am getting: make.link.gamlss : linkfun: no visible binding for global

If the code you are running in parallel is complicated, maybe foreach is not sophisticated enough to find all the variables you refer to. Maybe use parallel::clusterExport yourself? But be a aware that passing parameters is much safer than directly accessing globals in parallel processing, so this might just be your warning to not do that anyway. -- Sent from my phone. Please excuse my brevity.

Dear R helpers, I have following loss data and I need to fit LEFT truncated Log Normal distribution to this data which is Truncated at 1000000. dat = c(1333834,5710254,9987567,7809469,6940935,3473671,1270209,1102523,1124002, 5830159,4302300,3925242,2638409,2324421,7238436,9088709,7439250,4976551,4864319, 8741334,1863770,7098310,4942288,4971829,4986372) library(gamlss.tr) gen.trun(5, LOGNO)

Dear all and Mikis I have the opportunity to compare fits with the 'classical' glm and gamlss and no smoother of any kind just the same model formula (both with the binomial family). I get exactly the same coefficients but very different residuals, gamlss giving residuals which are extremely close to 'normal' and glm very far... How can this be ? Thanks in advance for

Hello: I'd like to know how and if the GLM convergence problems are addressed in gamlss. For simplicity, let's focus on Normal and Negative Binomial with log link. The convergence issues of the glm() function were alleviated in 2011 when glm2 package was released. Package gamlss was released in 2012, so it might still use the glm-like solution or call glm() directly. Is that the case or

Dear All: I have succeeded in fitting a GAMLSS.dist model to growth data I am working with it. My aim is to create a matrix of predicted percentiles and the corresponding the fitted model's sigma mu nu by agebins. Q: How do it generate these parameters as in L M S per Cole and Green 1992? Here are my working codes. Name of fitted model is gamlssfit > Agebin<-seq(6,36,6)

Hi, I'm playing around with gamlss and don't entirely understand the sigma result from an attempted lognormal fit. In the example below, I've created lognormal data with mu=10 and sigma=2. When I try a gamlss fit, I get an estimated mu=9.947 and sigma=0.69 The mu estimate seems in the ballpark, but sigma is very low. I get similar results on repeated trials and with Normal and

Hi Folks! Just started using the gamlss package and I tried a simple code example (see below). Why the negative sigma? John > y <- rt(100, df=1)> m1<-fitDist(y, type="realline")Warning messages:1: In MLE(ll3, start = list(eta.mu = eta.mu, eta.sigma = eta.sigma, : possible convergence problem: optim gave code=1 false convergence (8)2: In MLE(ll4, start = list(eta.mu =

Hi, I am new to bioconductor, trying to install KEGGSOAP package, but got warnings() when installing and error message when trying to load the package, can anyone suggest what went wrong? many thanks John > source("http://bioconductor.org/biocLite.R") Bioconductor version 2.11 (BiocInstaller 1.8.3), ?biocLite for help > biocLite("KEGGSOAP") BioC_mirror:

Dear all, I want to compare some different models for a dataset by QQ plots and AIC. I get the following AICs: - linear model: 19759.66 - GAMLSS model: 18702.7 - linear model with lognormal response: -7862.182 The QQ plots show that the lognormal model fits better than the linear model, but still much worse than the GAMLSS. So, in my opinion, the AIC of the lognormal model should be between the

Hello, I am using the package gamlss in R to plot repeated measurements. The command I am using is par.plot(). It works great except one thing about the label of the axises. I tried to label both x and y axises using ylab and xlab options. But the plot only gives variable variables. The labels did not show up. Below is the code I used. Any comments are appreciated! Thanks. library(gamlss)

I am wanting to change some lines of code in the R package named "nlme" http://cran.r-project.org/web/packages/nlme/index.html To do this I have downloaded the Package source named nlme_3.1-96.tar.gz, opened up the file and changed the text documents within the folder named R, specifically the cor.Struct.txt file. I now want to know how can I use this modified nlme_3.1-96.tar.gz file in