similar to: diagnostic information in glm. How about N of missing observations?

Dear R users: I assigned students to make some graphs and I'm having trouble answering some questions that they have. We are all working on R 2.1 on Fedora Core Linux 4 systems. 1. In the plot, the axis is not labeled by "numbers", but rather scientific notation like "-2e+08" or such. We realize that means -200,000,000. We want to beautify the plot. We would rather

Hello, everybody: My friends in Ukraine are starting a research lab at a national university and they asked what programs to use. I said "R" of course, and they then asked me 'what support does it have for Cyrillic'? i've done some snooping in the R website and all the references i find to foreign languages concern c and fortran, not Ukrainian or Russian. Since i'm an

I have a longitudinal data analysis project. There are 10 observations on each of 15 units, and I'm estimating this with randomly varying intercepts along with an AR1 correction for the error terms within units. There is no correlation across units. Blundering around in R for a long time, I found that for linear/gaussian models, I can use either the MASS method glmmPQL (thanks to

Greetings, R-help! On 2 Fedora Core 2 Linux systems, i've completely erased the previous R and all packages and then installed R-2.0 and installed fresh packages. In using Rcmdr, I see some trouble and I wonder if other people see this and if it is due to the tcl/tk, or R, or Rcmdr. (If readers have not yet tried Rcmdr, I recommend it not just because of the GUI it provides, but also

Last Friday, I noticed that it is difficult to work with regression models in which there are factors. It is easier to do the old fashioned thing of coding up "dummy" variables with 0-1 values. The predict function's newdata argument is not suited to insertion of hypothetical values for the factor, whereas it has no trouble with numeric variables. For example, if one uses a

Greetings: I'm running R-1.9.1 on Fedora Core 2 Linux. I tested a proportional odds logistic regression with MASS's polr and Design's lrm. Parameter estimates between the 2 are consistent, but the standard errors are quite different, and the conclusions from the t and Wald tests are dramatically different. I cranked the "abstol" argument up quite a bit in the polr

I'm writing R code to calculate Hierarchical Social Entropy, a diversity index that Tucker Balch proposed. One article on this was published in Autonomous Robots in 2000. You can find that and others through his web page at Georgia Tech. http://www.cc.gatech.edu/~tucker/index2.html While I work on this, I realize (again) that I'm a C programmer masquerading in R, and its really

Hello: would you please help me with the following glm question? for the R function glm, what I understand is: once you specify the "family", then the link function is fixed. My question is: is it possible I use, for example, "log" link function, but the estimation approach for the guassian family? Thanks, Shuangge Ma, Ph.D. ******************************************** *

Hello I am interested in Poisson or (ideally) Negative Binomial regression with an inflated number of 1 responses I have seen JK Lindsey's fmr function in the gnlm library, which fits zero inflated Poisson (ZIP) or zero inflated negative binomial regression, but the help file states that for ' Poisson or related distributions the mixture involves the zero category'. I had thought

Greetings Everybody: I generated a 1.2MB dta file based on the general social survey with Stata8 for linux. The file can be re-opened with Stata, but when I bring it into R, it says all the values are missing for most of the variables. This dataset is called "morgen.dta" and I dropped a copy online in case you are interested http://www.ku.edu/~pauljohn/R/morgen.dta looks like this

Hi Folks, I'm trying to find a neat solution to an apparently simple problem, but one which turns out to be a bit more intricate and tricky than one might expect. Suppose I have numbers given to a large number of digits. For example 1234567021 where (though I don't know this beforehand) only the last 3 digits will be varying (and all 3 will vary). What I want is, give a vector x of

Dear Friends in R: On RedHat linux, R-1.1, I've gotten far enough to create the graph that shows on the screen with 3 lines, but I have some trouble. Here is the way I created the three "overlaid" graphs: data<-read.table("DataCulture0",header=T,as.is = TRUE) attach(data) tmp1<-plot(acquaint~T,type='l', ylim=c(0,1),ylab="average

Using RedHat Linux 7.0, R-1.2.2, R-hdf5-1.2 library, I want to load a dataset, do some stuff with it, then erase its objects, get an other, repeat. My friend wrote a function which tried to clear away all the objects. At the end, it uses rm() to remove objects. This is the same way we do it interactively, from the R prompt: testLoadSeveralHDF <- function(numFiles) { for (i in

I'm looking for an analogy to SPSS and "variable lable" and "value lable" in R. I have a copy of S+4.0 and can't find any info in their docs, and don't find it in R-intro either. In SPSS, for each variable, there is a name like VAR001 and a variable lable (a longer descriptive string) like Respondent ID and for many of the values of other variables there are

Dear colleagues: I've been storing up this question for a long time and apologize for the length and verbosity of it. I am having trouble in consulting with graduate students on their research projects. They are using surveys to investigate the sources of voter behavior or attitudes. They have predictors that are factors, some ordered, but I am never confident in telling them what

Running R 1.1 on RedHat Linux 6.2. I need to write a shell script that goes through a bunch of directories of simulation output, creating summary files that have the mean and standard deviation of the variables found in the data files in each directory. I've got the R code doing almost the right thing. It reads in data, then gets the mean and standard deviation for the numeric variables,

Dear list, I've been messing around with coding functions in R and it just won't make sense to me. Running my analysis by hand on command line is fine and works but because of the repetitive nature of the job I would like to code a function for it. My problem: I would like to read in data from a file in my current working dir. so my code would look like: myanalysis <-

>>>>> On Mon, 25 Jul 2005 14:12:41 +0200, >>>>> Gorjanc Gregor (GG) wrote: > Hello R-users! > I have tried to use Sweave within LyX* and found two ways to accomplish > this. I have attached LyX source file for both ways as well as generated > PDFs. I have copied Gregor's files at http://www.ci.tuwien.ac.at/~leisch/Sweave/LyX for those who

I just heard a talk about a semi-parametric model. I was quite excited by the idea. This model is fitted y= xB + g(z) + e where x is a data matrix, B a column vector, z is another data matrix, and g is a smooth model fitted by a Kernel Smoothing regression (I got the idea any smoother would do as well). The speaker said that when z is considered as a "control" variable, and there is

Simple usage questions that I ought to be able to figure on my own, but can't. 1.I'm able to produce a cross tabulation table showing counts with either table or xtabs. But I want column percentages for interpretation, and it seems stupid to sit there with a calculator figuring marginals and column percentages. How to make R do it after this: > x <- c(1,3,1,3,1,3,1,3,4,4)