similar to: how to extract the original data of a glm object

Dear all, I am dealing with the following (apparently simple problem): For some reasons I am interested in passing variables from a dataframe to a specific environment, and in fitting a standard glm: dati<-data.frame(y=rnorm(10),x1=runif(10),x2=runif(10)) KK<-new.env() for(i in 1:ncol(dati)) assign(names(dati[i]),dati[[i]],envir=KK) #Now the following two lines work correctly:

Hello R users I ran more than 100 logistic regression analyses. Some of the analyses gave me this kind warning below. ########################################################### Warning messages: 1: algorithm did not converge in: glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, ... 2: fitted probabilities numerically 0 or 1 occurred in: glm.fit(x = X, y = Y,

dear all, This is a probably a silly question. If I type > grep("x",c("a.x" ,"b.x","a.xx"),value=TRUE) [1] "a.x" "b.x" "a.xx" Instead, I would like to obtain only "a.x" "b.x" How is it possible to get this result with grep()? many thanks for your attention, best, vito --

Dear all, It appears that MASS::polr() and Design::lrm() return the same point estimates but different st.errs when fitting proportional odds models, grade<-c(4,4,2,4,3,2,3,1,3,3,2,2,3,3,2,4,2,4,5,2,1,4,1,2,5,3,4,2,2,1) score<-c(525,533,545,582,581,576,572,609,559,543,576,525,574,582,574,471,595, 557,557,584,599,517,649,584,463,591,488,563,553,549) library(MASS) library(Design)

With version 8 of acrobat reader, it is now possible to have 3D in PDf documents. Does it exist already an R package who manage to produce 3D plots which can be saved as interactive 3D graphs in a PDF file? Best Regards Bruno Cavestro ------------------------------------------------------ Leggi GRATIS le tue mail con il telefonino i-mode? di Wind http://i-mode.wind.it/

Hello, I am currently working with the betareg package, which allows the fitting of a variable dispersion beta regression model (Simas et al. 2010, Computational Statistics & Data Analysis). I was wondering whether there is any package in R that allows me to fit variable dispersion parameters in the standard logistic regression model, that is to make the dispersion parameter contingent upon

Hi all, Could anybody recommend some easy-to-understand and example based notes/tutorials on how to use cubic splines to do filtering on multi-dimension data? I am confused by the 1-dimensional case, and more confused by multi-dimensional case. I found all the books suddenly become very abstract when it comes to this subject. They don't provide examples in R or Splus at all. Specifically,

I have estimated a multiple nonparametric regression using the loess command in R. I have also estimated an additive version of the model using the gam function. Is there a way of using the output of these two models to test the restrictions imposed by the additive model?

Hello all, I've been having trouble with assessing a breakpoint in a logistic GLM with two explanatory variables. For this analysis I've been using the 'segmented' package version 0.2-9.1. But I keep getting an error and I don't see where I would be going awry. The situation is the following: Two explanatory variables: bedekking - a variable with possible values between 0 and

Dear all, Is there *any* reason explaining what I describe below? I have the following line myfun(x) If I type them directly in R (or copy/past), it works.. However if I type in R 2.6.1 > source("code.R") ##code.R includes the above line Error in inherits(x, "data.frame") : object "d" not found namely myfun() does not work correctly. In particular the

dear all, Could anyone explain me the behaviour of median() within by()? (I am running R.2.7.0) thanks, vito > H<-cbind(rep(0:1,l=20),matrix(rnorm(20*2),20,2)) > by(H[,-1],H[,1],mean) INDICES: 0 V1 V2 -0.2101069 0.2954377 --------------------------------------------------------------------------------------------------------------------- INDICES: 1 V1

Dear list, I would like to do some calculation using different grouping variables. My 'df' looks like this: # Some data set.seed(345) id <- seq(200,400, by=10) ids <- sample(substr(id,1,1)) group1 <- rep(1:3, each=7) group2 <- rep(1:2, c(10,11)) group3 <- rep(1:4, c(5,5,5,6)) df <- data.frame(id, ids, group1, group2, group3) df <- rbind(df, df, df) df$time <-

hello, i have a problem. I want to upload a file with ajax and the following tag: submit_to_remote ''button_save'',''Speichern'',{ :url => {:action => ''ajax_update'', :id => @product}, :update => ''formular'' } it doesn''t work, my form_tag looks like: form_remote_tag(:url => {:action =>

Dear members, here is my trouble: My data consists of counts of trapped insects in different attractive traps. I usually use GLMs with a poisson error distribution to find out the differences between my traitments (and to look at other factor effects). But for some dataset where one traitment contains only zeros, GLM with poisson family fail to find any difference between this particular traitment

Hello dear subscribed Users, this is my first post, so please forgive me for any inconveniences. The following problem: I have a dataframe containing a factor column. For each column i would like to compare means as parted by the factor. Using the normal t.test function I have already achieved my goal. But i think, that for my original data, a permutational t.test would be better suited.

Hi. I'm a student at SFU in Canada. The basic thing I want to do is calculate means of different strata. I have 2 vectors. One has the values I want to take the means from, the other is the four strata I am interested in. So I essentially want to break up the information vector into the four strata and calculate four means, one for each stratum. How can I do this in a reasonable way? Thanks

I'm using the monoreg function (with weights) from the fdrtool package. How can I calculate the R square for this type of regression? Thanks for your help, Thierry -- View this message in context: http://www.nabble.com/R-square-for-Monotone-regression-tp15580803p15580803.html Sent from the R help mailing list archive at Nabble.com.

Is there a way to fit mixed proportional odds models in R? -- Using Opera's revolutionary e-mail client: http://www.opera.com/m2/

Hi, I am trying to creat a matrix with diagnal blocks, say, I have a matrix X of any dimension (nxm) ,and would like to have: X X X

Hi all, I'm having sometrouble with managing the seach path, in a function , I need to attach some data set at the begining and detach them at the end, say, myfunction<- function() { attach(mylist); ............. detach(mylist) } , the problem is, since I am still debugging this code, sometimes it got error and ended before reaching the end, thus the data is left in the