similar to: returned values of glim() in S PLus and glm() in R

Dear Experts, I need to calculate the cdf of the standard normal distribution, i.e. H(x) = 1/sqrt(2*pi) integral(exp(-z^2/2) dz), where z is b/w -infi to infi. I know there should be a way to do it in R, but did not know to do it. I'd appreciate any help you could offer. Charlie Liu Graduate student intern at EPA/ECO

Hi all, In my continuous transition of GLIM to R I try to make a glm with binomial errors. The data file have 3 vectors: h -> the factor that is ajusted (have 3 levels) d -> number of animais alive (the response) n -> total number of animals To test proportion of alive, make d/n. In GLIM: $yvar d$ $error binomial n$ $fit +h$ scale deviance = 25.730 (change = -9.138) at cycle 4

Dear All, THis is my "data.char$excluded" object and I want to show its content in my output screen. > data.char$excluded $names [1] "Species" "Target" "Sex" [[2]] [1] "DG" [[3]] [1] "R" [[4]] [1] "M" > When I run cat() in S Plus, I got: > cat(data.char$excluded, "\n") c("Species",

After some futile searches, I decided to ask the list to see if any of the sages out there would have an answer: I have a function I wrote a few years ago in S, which calls glim numerous times. I'd like to port it to R, but glm works differently from glim, which takes as part of its input an X design matrix. I probably could write a function to convert glim to glm, but hope this

Dear R People, I'm working on a plot function to produce the graph shown below. One of the features my supervisor does not like is that the labels in the Y- axix are shown vertically. Is there a way to change that to horizontally ? This is the axix() function I used : axis(2,at=seq(nstrat),labels=snames) The labels (snames) are: SEV1:HU:C, SEV1:MU:C, SEV1:MU:L, SEV1:RT:C and SEV1:RT:L,

Dear Expects, I tried to install the SJava package to the Library subdirectory of my R1.5.0. However, when I tried it according to the instructions from http://www.omegahat.org/RSJava/, I got the following error messages: library(SJava) Error in .Defunct() : `.Alias' is defunct. See ?Defunct. >.JavaInit() Error: couldn't find function ".JavaInit" I downloaded SJavaWin

Hi, I just downloaded the latest version of R - 1040. I'm doing the project of converting CATREG - a statistical software writen in S Plus to R. However, when I copied my R codes to the 1040 bin directory and resource my codes, I got the following error message, this never happened in my 1030 or 1010 versions of R. Anyone one know what's wrong with 1040? THanks CHarlie Liu EPA/ECO

Dear All, I wonder if anyone can advise me as to whether there is a consensus as to how the effect size should be calculated from GLIM models in R for any specified significant main effect or interaction. In investigating the causes of variation in infection in wild animals, we have fitted 4-way GLIM models in R with negative binomial errors. These are then simplified using the STEP procedure,

Hello, I would like to know if there is any package that allow us to fit Generalized Linear Models via Maximum Likelihood and Linear Models using Generalized Least Squarse in R as the functions glim and gls, respectively, from S-Plus. Also, anybody know if there is any package that fit Log-Linear Models using Generalized Least Squares? Any help will be very useful. Thanks, -- Frederico

Hi all I have another GLIM question. I have been using R as well as Genstat (version 6) in order to fit GLIM models to the data (displayed below). The same models are fitted but the answers supplied by the two packages are not the same. Why? Can anyone help? A discription of the data and the type of model/s fitted can be found below. Regards Allan The

I don't understand this behavior: > a <- c(0, 1, 2, 3) > b <- c(1, 2, 3, 4) > ifelse (a == 0, 0, b[a]) [1] 0 2 3 1 rather than the desired 0 1 2 3. Thanks for any explanation.

Hello! I have written an R script on a Windows platform where I calculate eight result matrices I plot using matplot. I would like to display the resulting plots successively, rather than simultaneously, and I was wondering if anyone could point me in the right direction as to how to do this. The graphs pop up in this manner by default when I run my script in S-PLUS, with tabs separating them so I

I've downloaded R for windows (9.0.1) and it is great! I've converted all my lecture notes for my GLM course to run on R (they are available on my web page below). I must admit I particularly like the default contrast options, which are identical to GLIM. Also I like the gl function - very useful! I have a couple of questions/bugs: 1. predict.glm doesn't work, but predict.lm does -

I'm having trouble figuring out how to create a function using "body<-" (). The help file for body() says that the argument should be a list of R expressions. However if I try that I get an error: > tmpfun <- function(a, b=2){} > body(tmpfun) <- list(expression(z <- a + b),expression(z^2)) Error in as.function.default(c(formals(f), value), envir) :

I came to R from GLIM and its glm. My data sets (ecological community data) are severely over-dispersed, and so I was delighted to find out that the MASS library has glm.nb which is an advancement from the GLIM macros I had used (N.E.Breslow, Applied Statistics 33, 38--44; 1984). However, I need to use offset, but that failed. I am not (yet --- hopefully) fluent enough in R to be able to

Hi All, I want to ask if there is a transpose function for data frame like the procedure of transpose in SAS? Because I want to partially transpose a data frame which contains 5 columns (siteid, date, time, obs, mod), what I want to do is to put time as the column variables along with siteid, and date, and put obs and mod in the row names. specifically to transpose a data frame: siteid date

I know R has a steep learning curve, but from where I stand the slope looks like a sheer cliff. I'm pawing through the available docs and have come across examples which come close to what I want but are proving difficult for me to modify for my use. Calculating simple group means is fairly straight forward: data(PlantGrowth) attach(PlantGrowth) stack(mean(unstack(PlantGrowth)))

Folks, I've run into trouble while writing functions that I hope will create and modify a dataframe or two. To that end I've written a toy function that simply sets a couple of variables (well, tries but fails). Searching the archives, Thomas Lumley recently explained the <<- operator, showing that it was necessary for x and y to exist prior to the function call, but I haven't

I'm trying to use R for some of the analysis shown in Box, Hunter and Hunter (1979, I believe) using the aov function. I'm using the first example in chapter 6, where they are determining the analysis of varience between 4 treatments. In this example, the are determineing the analysis between and within treatments, which I can get by aov(response~treatment+Error(treatment)) Where

Greetings, I have a meta-analysis problem in which I have fixed effects regression coefficients (and estimated standard errors) from identical models fit to different data sets. I would like to use these results to create pooled estimated regression coefficients and estimated standard errors for these pooled coefficients. In particular, I would like to estimate the model \beta_{i} = \mu +