similar to: posting for r-help

There may be a bug in the anova.glm function. deathstar[32] R R : Copyright 2004, The R Foundation for Statistical Computing Version 2.0.1 (2004-11-15), ISBN 3-900051-07-0 R is free software and comes with ABSOLUTELY NO WARRANTY. You are welcome to redistribute it under certain conditions. Type 'license()' or 'licence()' for distribution details. R is a collaborative project

Hi Community, I'm trying to reconcile Cook's Distances computed in glm. The following snippet of code shows that the Cook's Distances contours on the plot of Residuals v Leverage do not seem to be the same as the values produced by cooks.distance() or in the Cook's Distance against observation number plot. counts <- c(18,17,15,20,10,20,25,13,12) outcome <- gl(3,1,9)

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 +

I don't have a copy of Dobson (1990) from which the glm.D93 example is taken in example("glm"), but I'm strongly suspecting that these are made-up data rather than real data; the means of the responses within each treatment are _identical_ (equal to 16 2/3), so two of the parameters are estimated as being zero (within machine tolerance). (At this moment I don't understand

Hi! The nobs() method for glm objects always returns the number of cases with non-null weights in the data, which does not correspond to the number of observations for Poisson regression/log-linear models, i.e. when family="poisson" or family="quasipoisson". This sounds dangerous since nobs() is, as the documentation states, primarily aimed at computing the Bayesian

Dear list, I just hit an error that stopped my make && make check-devel operation on my linux box (FC3, i686 P4 2GB RAM). Just to note that I've been building the development branch(?) for some time and this is the first hint of a problem. 1) updated the src tree using svn update 2) ran ../configure --with-recommended-package=no from my build directory 3) got: R is now configured

Hello, I'm learning to use Sweave, and I've run into a problem: sometimes, when entering long lines of input and using long variable names, Sweave will not insert linebreaks in a way that respects the width setting. This causes undesirable overflows into the margins in the latex file. For example, consider the following document (adapted from the GLM example): \documentclass{article}

Following p.206 of "Statistical Models in S", I wish to change the code for summary.glm() so that it estimates the dispersion for binomial & poisson models when the parameter dispersion is set to zero. The following changes [insertion of ||dispersion==0 at one point; and !is.null(dispersion) at another] will do the trick: "summary.glm" <- function(object, dispersion =

Greetings, I am running glm models for species counts using a poisson link function. Normal summary functions for this provide summary statistics in the form of the deviance, AIC, and p-values for individual predictors. I would like to obtain the p-value for the overall model. So far, I have been using an analysis of deviance table to check a model against the null model with the intercept as

Hello R users I like to extract z values for x1 and x2. I know how to extract coefficents using model$coef but I don't know how to extract z values for each of independent variable. I looked around using names(model) but I couldn't find how to extract z values. Any help would be appreciated. Thanks TM ######################################################### >summary(model) Call:

the data file has such structure: 1992 6245 49 . . 20 1 0 0 8.739536 0 . . . . . . . . "alabama" . 0 . 1993 7677 58 . . 15 1 0 0

OK, I really dread to ask that .... much more that I know some discussion about p-values and if they are relevant for regressions were already on the list. I know to get p-val of regression coefficients - this is not a problem. But unfortunately one editor of a journal where i would like to publish some results insists in giving p-values for the squared deviance i get out from different glm and

Hi there, I am new to the package glmmadmb, but need it to perform a zero-inflated gzlmm with a binomial error structure. I can't seem to get it to work without getting some strange error messages. I am trying to find out what is affecting the number of seabird calls on an array of recorders placed at 4 sites on 6 islands. I have nightly variables (weather and moonlight), site variables

Hi all I am preparing a document using Sweave; a really useful tool. But I am having a problem. Consider this toy example Sweave file: \documentclass{article} \begin{document} <<echo=TRUE,results=verbatim>>= options(width=40) # Set width to 40 characters hide <- capture.output(example(glm)) # Create an example of the problem, but hide the output summary(glm.D93) #

Is there a trick to listing available providers? I can''t find it.

This message is in MIME format. The first part should be readable text, while the remaining parts are likely unreadable without MIME-aware tools. --27464147-1557463723-1147085467=:8118 Content-Type: TEXT/PLAIN; charset=iso-8859-1; format=flowed Content-Transfer-Encoding: 8BIT On Mon, 8 May 2006, x.sole at iconcologia.net wrote: > Full_Name: Xavier Sol? > Version: 2.3.0 > OS: Windows

I am attempting to run a glm with a binomial model to analyze proportion data. I have been following Crawley's book closely and am wondering if there is an accepted standard for how much is too much overdispersion? (e.g. change in AIC has an accepted standard of 2). In the example, he fits several models, binomial and quasibinomial and then accepts the quasibinomial. The output for residual

Dear list, Can anyone tell me how to obtain the rank of a sparse Matrix, for example from package Matrix (class dgCMatrix)? Here is an example of QR decomposition of a sparse matrix (from the sparseQR class help). library(Matrix) data(KNex) mm <- KNex$mm str(mmQR <- qr(mm)) Similarly, using the functions/classes from the relatively new MatrixModels package: library(MatrixModels)

THANKS so very much for your help (previous and future!). I have a two follow-up questions. 1) You say that dispersion = 1 by definition ....dispersion changes from 1 to 13.5 when I go from binomial to quasibinomial....does this suggest that I should use the binomial? i.e., is the dispersion factor more important that the 2) Is there a cutoff for too much overdispersion - mine seems to be

Peter Thank you for the information. I accidentally deleted Ken's post without having read it. Ken' s thought is great but as you said awful to implement I thought that capture.output would come in handy some time when I first saw it on an unrelated reply. Just thought :- the latex listings package may have alternatives If I remember correctly it has wrapping and other goodies but I