similar to: glm inconsistent behaviour (PR#5213)

A querent on StackOverflow asked about the with() function http://stackoverflow.com/questions/42283479/why-when-to-use-with-function#42283479 and asked about the example in ?with library(MASS) with(anorexia, { anorex.1 <- glm(Postwt ~ Prewt + Treat + offset(Prewt), family = gaussian) summary(anorex.1) }) which saves little or no typing

Hello, I'm a starting user of R. I have installed R 1.9.1 and winedt 5.4 If I run the example from written with winedt. The summary command does not produce any output. It does when I repeat the command manualy in R. Can someone explain me what can be the problem? library(MASS) data(anorexia) anorex.1 <- glm(Postwt ~ Prewt + Treat + offset(Prewt), family =

Dear Listers, I got this message when compiling a package: * creating pgirmess-manual.tex ... OK * checking pgirmess-manual.text ... ERROR LaTex errors when creating DVI version. This typically indicates Rd problems. The message is quite explicit but I struggled a lot before understanding that the trouble comes from a single file "selMod.rd" among 44 topics. Even though I have

Dear all, I am fitting a GLM similar to library(MASS) anorex.1 <- glm(Treat~Postwt+Prewt,family = binomial, data = anorexia) I have found two ways of computing the p-value of the fitted model: pval1 <- 1-pchisq(anorex.1$deviance,anorex.1$df.residual) pval2 <- 1-pchisq(anorex.1$null.deviance - anorex.1$deviance, anorex.1$df.null - anorex.1$df.residual) pval2 is

With new "strict" settings in R-devel, the following glm() example > data(anorexia, package = "MASS") > fm <- glm(Postwt ~ Prewt + Treat + offset(Prewt), family = gaussian, data = anorexia) > methods(class = class(fm)) Warning in grep(name, row.names(info)) : argument 'pattern' has length > 1 and only the first element will be used Warning in

Dear all, After running a glm, I use the summary ( ) function to extract its coefficients and related statistics for further use. Unfortunately, the screen only displays a small (last) part of the results. I tried to overcome the problem by creating/saving an object "coef" for coefficients of the model and export/save it e.g. as a cvs document. While I succed with this operatiion, I do

Dear listers, I was used to package pgirmess under Windows with everything OK, but, for the first time, I had a trial this afternoon on Ubuntu 7.10 gutsy (I have a double boot computer and work more and more under unix) and R 2.7.0. Everything went OK except this: sudo R CMD check pgirmess ..... * checking examples ... ERROR Running examples in 'pgirmess-Ex.R' failed. The error most

I think this would be a good change. I think most users use the 'methods(class = <...>)' function to answer the question, "what methods can I call on objects with these classes?", and in that context I think it would be sensible for the function to accept more than one class. Kevin On Wed, Oct 17, 2018 at 7:15 AM Martin Maechler <maechler at stat.math.ethz.ch>

Hi, I looking for a method that use F or Chisq test instead of AIC in a stepwise modelo selection. I try the grasp package using the grasp.step.anova, but It dont work. > library(grasp) Carregando pacotes exigidos: gam Carregando pacotes exigidos: splines Carregando pacotes exigidos: mda Carregando pacotes exigidos: class > data(anorexia,package="MASS") > > m1 <-

R-1.7.0 built on NetBSD 1.6, but the validation test suite failed: Machinetype: Intel Pentium III (600 MHz); NetBSD 1.6 (GENERIC) Remote gcc version: gcc (GCC) 3.2.2 Remote g++ version: g++ (GCC) 3.2.2 Configure environment: CC=gcc CXX=g++ LDFLAGS=-Wl,-rpath,/usr/local/lib make[5]: Entering directory `/local/build/R-1.7.0/src/library' >>> Building/Updating

Dear all, I have installed 1.7.0 on my Win XP and want to use MASS. But I get this error message: > library(MASS) Error in namespaceExport(ns, exports) : undefined exports: abbey, accdeaths, Aids2, Animals, anorexia, austres, bacteria, beav1, beav2, biopsy, birthwt, ... Error in library(MASS) : package/namespace load failed I therefore again downloaded VR.zip. When I extracted the files I

I'm pretty sure I'll feel like [more of] an idiot but... Using Rgui working in a fresh, blank directory. > require(MASS) Loading required package: MASS [1] TRUE > data(cabbages) Warning message: ======> Data set `cabbages' not found in: data(cabbages) <===== > ls() [1] "last.warning" > search() [1] ".GlobalEnv" "package:MASS"

Hi all, I am using RODB to export multiple data.frames into one excel file with multiple sheets. One thing I can't seem to unserdatand is way the command adds the character: ' To the beginning of each of my (non numeric) values. Here is an example code: library(RODBC) library(MASS) data(anorexia) save2excel <- function(x, t.name) sqlSave(xlsFile, x, tablename = t.name, rownames =

Ben Bolstad experienced something odd while running R CMD check over a package of ours using r-devel (yesterday's fresh). He tracked down the problem to a vignette calling 'library(MASS)'. Please kindly ignore if this is a known (and temporary) issue. Laurent ----- Forwarded message from Ben Bolstad <bolstad@stat.berkeley.edu> ----- Return-Path:

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Hi, we have this model glm(CPUE~Year+Month+Length+Year:Month, family=Gamma (link="inverse")) where, CPUE is a numerical variable >0, We use this model for standardization of CPUE and we need the new estimates for each year. How can we obtain it? Thank you

Dear all,    I am having a recurring problem when I attempt to conduct a GLM.  Here is what I am attempting (with fake data): First, I created a txt file, changed the directory in R (to the proper folder containing the file) and loaded the file: #avoid<-read.table("avoid.txt",header=TRUE);avoid #  treatment feeding avoid noavoid #1   control  nofeed     1     357 #2  

Dear all, I have question regarding GLMs: I have a discrete response variable and a continuous explaining variable. Like this: http://www.myimg.de/?img=example1db0f.jpg I want to use a GLM to investigate. I have to specify the "familiy of the distribution of the response variable" - or, maybe more precise, the "family of the distribution of the residuals of the response

This is a wrapper around gnm by Turner and Firth to make fitting log-multiplicative models as convenient as possible: it provides simple functions, good starting values, jackknife or bootstrap standard errors, and direct plotting of the results. In addition, it makes it possible to identify scores from RC(M) association models, which gnm does not allow without computing the SVD yourself. It will

This is a wrapper around gnm by Turner and Firth to make fitting log-multiplicative models as convenient as possible: it provides simple functions, good starting values, jackknife or bootstrap standard errors, and direct plotting of the results. In addition, it makes it possible to identify scores from RC(M) association models, which gnm does not allow without computing the SVD yourself. It will