similar to: glm crash (PR#197)

Dear R-helpers, Im trying to fit a Log-linear model on a dataset with bird counts from 60 sites over 14 years for 12 months each (factors for the models). One of the aims is to predict the missing values in this dataset with model predictions. Ive first tried to work with GLM's, that worked fine except for models with one or more interaction-terms. The GLMs run, run .. for hours. So I

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

================================================= This is an automated summary of the status of the R-bugs repository. Note that this may be neither complete nor perfectly correct at any given instance: Not all bugs are reported, and some reported bugs may have been fixed, but the repository not yet updated. Some bug fixes are difficult to verify because they pertain to specific hardware or

I am trying to fit a GLM model using R (version 0.64.1 Win95) onto a dataframe(dtse) consisting of 3348 rows with 4 variables: - 3 factors: (c)31 levels, (m)12 levels (s)9 levels) - 1 integer: (n) The data consists of counts and is strongly overdispersed. I try fit the following model dtse.glm<- glm(n~s+c+m, data=dtse, family=quasi(link=log, variance=mu)) When I issue this command R sometimes

Hello, This is a standard example in which I read the time series data from a csv file and create a zoo object: x0 <- read.csv(file="CPI.csv", header=TRUE) time_0<-as.yearmon("1981-01")+(0:371)/12 x0zoo<-zoo(x0, time_0) The data look like this: TIME CPI CPI_food CPI_Clothes CPI_House CPI_Rent 198101 62.1 55.34 103.45 65.24 61.43 198102 63.16 56.95

The current llvm/llvm-gcc-4.2 2.6 branch passes all of the Polyhedron 2005 benchmarks built with its gfortran. The results compare as follows... Compile Command : gfortran -ffast-math -funroll-loops -msse3 -O3 %n.f90 -o %n benchmark gcc-4.2.4 llvm-gcc-svn llvm-gcc-2.6 llvm-gcc-2.6 at -m32 20081031 -m32 at -m32 at -m64 ac 18.30

Hi, I have a dataset of historical monthly temperature data that is grouped by weather station. I want to create z-scores of the monthly data using a base period of a subset of years. I subset the dataset first to include only data from the years (V2) that make up the base period so I could calculate the appropriate means and standard deviations V1 V2 V3 V12 V15 V16 V19 84

Hi, I have a dataframe basically like this: > head(asturias.gen2011[,c(1,4,9:14)]) municipio total upyd psoe pp iu fac tipo 440 Allande 2031 1.44 31.10 39.75 4.01 21.62 1000-10000 443 Aller 12582 1.37 33.30 37.09 15.53 10.35 10000-50000 567 Amieva 805 1.48 32.69 37.36 6.15 20.16 <1000 849

Codeweavers offers downloads of its Crossover Games for $39.95 and Crossover Professional for $69.95 but if you apply coupon code "CrossOverNow" this will drop CrossOver Games to $27.96 And Crossover Professional to $48.96 That's 30% off the normal retail selling price. CrossOver enables you to install Windows applications and games on Intel-based Macs and Linux. CodeWeavers also

Just monkey patched Sprockets in our Rails 3.2.9 app to override the Cache-Control header for html assets that we need to tweak more often in development, but that we don''t want to use digests/fingerprinting with: # Sprockets 2.x patch if Rails.env.development? module Sprockets module Server private alias_method :sprockets_headers, :headers def headers(env,

Nadav (or anyone who is familiar with the loop vectorizer), Does the current loop vectorizer inquire about the SIMD capabilities of the target architecture when it decides whether it is profitable to vectorize a loop? I am asking this because I would like to have loop vectorization disabled for targets that don't support SIMD instructions (for example, standard mips32). Loop vectorization

Hi see in line > -----Original Message----- > From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Courtney > Benjamin > Sent: Thursday, August 10, 2017 5:55 AM > To: r-help at r-project.org > Subject: [R] Creating New Variable Using Ifelse > > Hello R Help List, > > I am an R novice and trying to use the ifelse function to create a new binary >

This message is about a curious difference in timing between two ways of computing the same function. One uses expm, so is expected to be a bit slower, but "a bit" turned out to be a factor of >1000. The code is below. We would be grateful if anyone can point out any egregious bad practice in our code, or enlighten us on why one approach is so much slower than the other. The problem

Hi All, We've been working on enhancing LLVM's instrumentation based profiling by adding indirect call target profiling support. Our goal is to add instrumentation around indirect call sites, so that we may track the frequently taken target addresses and their call frequencies. The acquired data has uses in optimization of indirect function call heavy applications. Our initial findings

Hai Dirk, Thank your for the reply, most welkom. > -----Oorspronkelijk bericht----- > Van: Dirk Streubel [mailto:dirk.streubel at posteo.de] > Verzonden: maandag 23 maart 2020 9:59 > Aan: L.P.H. van Belle > Onderwerp: Re: [Samba] Debian Buster Samba 4.12 (experimental > packages) amd64/i386 > > Hello Louis, > > i have here a Workstation with Fedora 31 and

All - I'm having an issue with trying to plot a model derived from nls() onto a simple plot.? I have included a sample data set and the code that I've been using. ?? year month day?????? date location mileage? cost gallon????? cpg ? mpg????????? x 2009???? 1?? 4?? 1/4/2009????? BZN? 124585 19.39? 14.37 1.349339 10.71677 2009-01-04 2009???? 1? 15? 1/15/2009????? BZN? 124888? 23.2? 16.12