similar to: List arguments from data frame columns in formula

Hello, I have some trouble using step() and stepAIC() functions. I'm predicting recruitment against several factors for different plant species using a negative binomial glm. Sometimes, summary(step(model)) or summary(stepAIC(model) does not select the best model (lowest AIC) but just stops before. For some species, step() works and stepAIC don't and in others, it's the opposite.

Hi, I have a large matrix (SNPs) that I want to cycle over with logistic regression with interaction terms. I have made a loop but I am struggling to identify to the formula the name of the column in a way which is meaningful to the formula. It errors becasue it is not evaluated proporly. (below is a pilot with only 7 to 33 columns, my actual has 200,000 columns) My attempts: for (i in 7:33)

I'm trying to configure Squid ntlm autentication on Samba4 DC. I followed Squid and Samba's documentation and i got success when I login with user natalia.silva, but if I log with natalia.vaz i get the error -- Nat?lia Vaz Silva Administradora de redes

Hello, I was using version 2.13.2 and I have just downloaded the latest version 2.14.1. However, I''m trying to install the packages I was using and when I look for them in the packages list, I can´t find many in the CRAN binaries (e.g. "vegan"). I do find them in the CRAN sources but the installation fails. I tried downloading the version 2.14.0 and I had the same problem. I

Hello R-users. I haven't use R for a life time and this might be trivial - I hope you do not mind. I have a questions about arguments in the Glm-function. There seems to be something that I cannot cope. The basics are ok: > y <- as.double(rnorm(20) > .5) > logit.model <- glm(y ~ rnorm(20), family=binomial(link=logit), trace = TRUE) Deviance = 28.34255 Iterations - 1

Dear all, I'm using R version 3.2.0 in Ubuntu 12.04 LTS. While trying to install any package I get the error: "/usr/bin/ld: cannot find -lgfortran" If I open a Terminal and run "ldconfig -p | grep libgfortran"?, I get:? "libgfortran.so.3 (libc6,x86-64) => /usr/lib/x86_64-linux-gnu/libgfortran.so.3" I've been an R user for two years and this is the

With ggplot2, I can plot the glm stat_smooth for binomial data when the response is binary or a two-level factor as follows: data("Donner", package="vcdExtra") ggplot(Donner, aes(age, survived)) + geom_point(position = position_jitter(height = 0.02, width = 0)) + stat_smooth(method = "glm", family = binomial, formula = y ~ x, alpha = 0.2, size=2) But how can I

Hello, I use lme4 package. library(lme4) fit=lmer(y ~ time+dye+trt+trt:time + (1|rep), data=dataset, na.action='na.omit') anova(fit) The anova gives sequential F-tests and sequential SS. My question is: how I can get partial F-tests and partial SS? For lm (not lmer) anova(lm(y~x+z)) we can use anova(fit, ssType=3) but it is not work for lmer. Natalia.

Hello all, I have data: Genes time rep vart dye y trt 130911 sa1-d07 030min 1 col g 9.636244 o 145771 sa1-d07 030min 1 col r 8.107577 c 93335 sa1-d07 030min 1 ler g 7.409566 o 94821 sa1-d07 030min 1 ler r 5.107160 c 10119101 sa1-d07 030min 2 col g 8.336862 o 11605101 sa1-d07 030min 2 col r 7.824530 c 725313 sa1-d07

Hello, I make a samba server + ldap. I create some users and get login in mydomain with success. After login I can't write in paste user.But is denied. #some users created brasil:x:1012:513:Brasil Telhados:/dev/null:/bin/false atleticomg:x:1013:513:Clube Atletico MG:/home/atleticomg:/bin/bash #groups crated informatica:*:1001:atleticomg,natalia,faria

Hi List, I'm trying to built a list where there are some missing data in some columns, then I would like to know what I should put in these blank spaces when building the vector. eg: color<- c("red",?,"orange","green",?,?,?) size<- c(2,1,?,3,?,?,8) Thanks, Natalia [[alternative HTML version deleted]]

I am hoping to create a graph that will look like it is plotted on arithmetic probability plot. Something similar to how this is done in Excel: http://peltiertech.com/Excel/Charts/ProbabilityChart.html. I can't quite find a code that will transform the linear axis into a cumulative percent axis with an arithmetic probability. And I am not good enough at R to do that myself. Any help will be

Dear all, I've been reading for many days trying to predict with lmer but I haven't managed to do it. I've fitted an allometric model for trees where I have included climatic variables and diameter in the fixed part and in the random part I've included the experimental sites where trees are and also their provenance region. The model is like this :

Hello, I have some "stupid" problems managing "date" data. I have a colomn "date", which I converted from a character representation: for example: a="26/02/06" date=strptime(a,format="%d/%m/%y") For one part of the analysis, I'm interested only in the month and the year, so I did: m.y=strftime(date,format="%m/%y") This returns me

Hello all, I have problem with setting up random effects. I have a model: y=x1+x2+x1*x2+z1+z1*x2 where x1, x2, x1*x2 are fixed effects and z1, z1*x2 are random effects (crossed effects) I use library(nlme) 'lme' function. My question is: how I should set up random effects? I did lme(y~x1+x2+x1:x2, data=DATA, random=~z1+z1:x2, na.action='na.omit') but it did not work.

Dear list, After running for a while, it crashes and gives the following error message: can anybody suggest how to deal with this? Error in if (ratio0[i] < log(runif(1))) { : missing value where TRUE/FALSE needed ################### original program ######## p2 <- function (Nsim=1000){ x<- c(0.301,0,-0.301,-0.602,-0.903,-1.208, -1.309,-1.807,-2.108,-2.71) # logdose

I am trying to write a wrapper for the last example in help(cv.glm) that deals with leave-one-out-cross-validation (LOOCV) for a logistic model. This wrapper will be used as part of a bigger program. Here is my wrapper funtion : logistic.LOOCV.err <- function( formu=NULL, data=NULL ){ cost.fn <- function(cl, pred) mean( abs(cl-pred) > 0.5 ) glmfit <- glm(

Dear R Mailing Subscribers, I just have a question of how R handles interacting variables in model creation using glm for instance. if I write : >> model=glm(solution~descriptor1+descriptor2+descriptor3,family=binomial(link="logit")) I should end up with coefficients for a logistic model that I can introduce easily in the mathematical form of such a model (weighted sum of

Hello dear r-gurus! I have a question about the logit-model. I think I have misunderstood something and I'm trying to find a bug from my code or even better from my head. Any help is appreciated. The question is shortly: why I'm not having same coefficients from the logit-regression when using a link-function and an explicite transformation of the dependent. Below some details. I'm

glm(A~B+C+D+E+F,family = binomial(link = "logit"),data=tre,na.action=na.omit) Error in `contrasts<-`(`*tmp*`, value = "contr.treatment") : contrasts can be applied only to factors with 2 or more levels however, glm(A~B+C+D+E,family = binomial(link = "logit"),data=tre,na.action=na.omit) runs fine glm(A~B+C+D+F,family = binomial(link =