similar to: (no subject)

Hello, I am writing as an administrator, not as an R user, so forgive me if I am not completely knowledgeable about R. I have a user who is creating an R package for windows from a Linux environment using the crossbuild environment by Jun Yan and A.J. Rossini. The packages she generated worked fine until she tried to install in R 1.9.1 for Windows. Now when she installs with

Dear R-user: After the fitting the Tobit model using zelig, if I use the following command then I can get the regression coefficents: beta=coefficients(il6.out) > beta (Intercept) apache 4.7826 0.9655 How may I extract the "Naive SE" from the following output please? > summary(il6w.out) Call: zelig(formula = il6.data$il6 ~ il6.data$apache, model =

Greetings all, please consider the following data: #Build Data frame Slope<-c(1.291370, 12.208500, 2.110930, 0.578990, 5.019520, 0.807444, 0.554079 , 1.257080, 0.241504 , 0.184337 , 0.383044 , 0.342021) Exposure<-c(790.54, 1167.79 , 845.58 , 1082.47 , 1189.61 , 677.17 , 2058.56 , 469.09 , 112.02 , 803.31 , 254.14 ,1336.16) FwyDist<-c(11809.4222 ,10623.0458, 12279.6271,

our group at Duke is currently attempting to connect two data sets fed through a web-based system, one containing research questions (i.e., variables positioned with certain roles) and a database of statistical methods. this connection is done informally in a number of R packages and related software such as Rcmdr, R4calc, and Rkward where a variable of a certain type is matched to a certain

Hi, y is nominal (3 categories), x1 to 3 is scale. What I want is a regression, showing the probability to fall in one of the three categories of y according to the x. How can I perform such a regression in R? Thanks for your help S?ren

Pls advise how I can use R in conjoint analysis?? regds Faisal Afzal Siddiqui Karachi, Pakistan ____________________________________________________________________________________ Looking for last minute shopping deals?

I have found the "simulate" method (incorporated in some packages) very handy. As far as I can tell the only class for which simulate is actually implemented in base R is lm ... this is actually a little dangerous for a naive user who might be tempted to try simulate(X) where X is a glm fit instead, because it defaults to simulate.lm (since glm inherits from the lm class), and the

I use mnp to run a multinominal probit regression model, but the summary doesn't contain the model statistics, such as the log-likelihood and degree of freedom, for the assessment of the goodness-of-fit of the fitted model. Is there any way that I can generate these statistics for the fitted model in R? Many thanks in advance! SC

Hello all, if I have multiple imputed data sets, is there a command or function in R in any package you know of to combine those, I know one common MI approach is rubins rules, is there a way to do this using his rules or others? I know theres ways, like using Amelia from Gary King's website to create the imputed data sets, but how to make them into one or combine them for analysis.

Ein eingebundener Text mit undefiniertem Zeichensatz wurde abgetrennt. Name: nicht verf?gbar URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120604/b313c7fa/attachment.pl>

Dear R-help, I was bitten by the behavior of all() when given logical(0): It is TRUE! (And any(logical(0)) is FALSE.) Wouldn't it be better to return logical(0) in both cases? The problem surfaced because some un-named individual called randomForest(x, y, xtest, ytest,...), and gave y as a two-level factor, but ytest as just numeric vector. I thought I check for that in my code by testing

Hi, I'm having problems with the Zelig package - when using the below R displays the follwing message (I'm running R i386 2.15.3 for Windows and have updated all the Zelig packages): z.out<-zelig(Surv(psurv2, pcens2) ~ ren_sup3 + age, data=data_urgent, model="coxph") ** The model "coxph" is not available with the currently loaded packages, ** and is not an

Hi Folks, According to the PDF file blogit.pdf in the Zelig documentation: "Use the bivariate logistic regression model ["blogit"] if you have two binary dependent variables (Y1,Y2), and and wish to model them jointly as a function of some explanatory variables. Each pair of dependent variables (Yi1,Yi2) has four potential outcomes, (Yi1=1,Yi2=1), (Yi1=1,Yi2=0),

hello all I am using the R package Zelig for some tobit regression with robust standard errors. I have got R version 2.9.2 (2009-08-24) and Zelig Version: 3.4-5 when i do demo(robust) It ends like this way data(coalition) > # Fit the model with robust standard error > user.prompt() Press <return> to continue: > z.out3 <- zelig(Surv(duration, ciep12) ~ polar + numst2 +

If I do > example(lm) ... > mycoef <- function(object, ...) UseMethod("coef", object) > mycoef(lm.D9) Error in mycoef(lm.D9) : no applicable method for "coef" which is pretty surprising, as coef has a default method. After a bit of digging, this comes from do_usemethod having defenv = environment where the generic was defined */ defenv =

Hello, would someone please help explain the following inconsistency in the if/else statement to me? The format of the if/else #3 below is ok, but if/else #1 is not? (I get an "unexpected else" type error.) In order for it to work I have to use if/else #2 Thanks .. maybe there is some reason for this, but this looks very inconsistent to me. R version 2.10.1 (2009-12-14) Ubuntu 9.04

Dear list members, Is there a package somewhere for jointly estimating two poisson processes? I think the closest I've come is using the "SUR" option in the Zelig package (see below), but when I try the "poisson" option instead of the "SUR" optioin I get an error (error given below, and indeed, reading the documentation of the Zelig package, I get the impression

I'm running a multinomial logit in R using the Zelig packages. According to str(trade962a), my dependent variable is a factor with three levels. When I run the multinomial logit I get an error message. However, when I run 'model=logit' it works fine. any ideas on whats wrong? ## MULTINOMIAL LOGIT anes96two <- zelig(trade962a ~ age962 + education962 + personal962 + economy962 +

Hi all, I have a dataset with a response variable with three categories (1, 2, 3) and a lot of continuous variables. I'd like to make a MLR with these variables. I've been watching the libraries nnet and zelig for this purpose but I don't understand them well. I use a training sample data to make the MLR. train.set <- sample(1:1000,1000*0.7) I have done this: library(nnet) net

install.packages works for Linux because the directory structure is not version dependent, as it is for the Windows download. That should be fixed as soon as my sys admin consents to install R 1.9.0 so we can do the cross compile. Of course, you are right, Martin and Peter, that Zelig should be on CRAN proper. We just need to write a few .Rd files to be compliant with R check, and change our