similar to: R 1.9.1 package installation problems

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 =

Could you help me with a problem? I should put non-linear variables into zelig-model, how can that be done? I'm dealing with air pollution data, trying to find out daily associations between mortality and air pollutants. Weather variables used as confounders are in some cases non-linear. Since smoothing is not an option I don't know how to proceed. Thanks, Jaana

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,

Hello All, I am building llvm-clang cross tool chain for arm target, after successful build for Linux host now I am now building toolchain for *arm target*. However, I am getting below error message which seems to be confusing and not getting any idea how to resolve this issue. *Command :* #CC='clang' CXX='clang++' cmake -G Ninja /home/iiita/crossbuild/llvm

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

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?

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

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

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 +

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, When compiling R-2.0.0 for cross-compiling, I get the following error when calling 'make R' ---------- Making package base ------------ adding build stamp to DESCRIPTION /bin/sh: line 1: --vanilla: command not found make[5]: *** [frontmatter] Erro 127 make[4]: *** [all] Erro 2 make[3]: *** [pkg-base] Erro 2 make[2]: *** [rpackage] Erro 2 make[1]: *** [all] Erro 2 make[1]:

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

Zelig: Everyone's Statistical Software Kosuke Imai, Gary King and Olivia Lau Version 1.0 (Available at http://gking.harvard.edu/zelig) A growing proportion of statisticians and methodologists from many disciplines are converging on R, a powerful statistics package and programming language. As an open source project, R is freely

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

Hi, I'm trying to model an ARMA(1,[1,4]), i.e. I want only lags 1 and 4 of the Moving Average part. It's the '[1,4]' part that is giving me a problem. I've tried different arma's and arima's in different packages, namely: packages tseries, fArma, FinTS, timeSeries, TSA, Zelig, ds1, forecast For example, with package FinTS: > ( ARIMA(y, order=c(1,0,c(1,4))) )

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