similar to: Package zelig

Dear all, I have question but cannot explain without providing some context first: I want to calculate how many policy-connected coalitions between 7 parties are possible. I have positions on an one-dimensional scale for each party and I have sorted the parties on the positions (it is sorted from extreme left to extreme right, hence using a left-right scale). A policy-connected coalition

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

hello, I am using the following code >s<-"I am very happy, excited, and optimistic.I am very scared, annoyed, and irritated.Iraq?s political crisis entered its second week one step closer to the potential.dissolution of the government, with a call for elections by a vital coalition partner and a suicide attack that extended the spate of violence. that has followed the withdrawal.of

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 =

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),

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, I request help with the following: INPUT: A data frame where column "Lower" is a character containing numeric values (different count or occurrences of numeric values in each row, mostly 2) > dput(dd) structure(list(State = c("Alabama", "Alaska", "Arizona", "Arkansas", "California"), Lower = c("R 72?33",

Hi RUsers, Suppose I want to see the data on the website url <- "http://www.nseindia.com/content/indices/ind_histvalues.htm" for the index "S&P CNX NIFTY" for dates "FromDate"="01-11-2010","ToDate"="02-11-2010" then read the html table from the page using readHTMLtable() I am using this code webpage <-

Hey guys, I have a doubt here , It is something simple I guess, what am I missing out here ?? f <- function(y) function() y tmp <- vector("list", 5) for (i in 1:5) tmp[[i]] <- f(i) tmp[[1]]() # returns 5; z <- f(6) tmp[[1]]() # still returns 5; it should return 6 "ideally" right ??? Even if I dont evaluate the function tmp[[1]] before i.e I do rm(list=ls()) f

## Continuing with your data AA <- stringr::str_extract_all(dd[[2]],"[[:digit:]]+") BB <- lapply(AA, as.numeric) ## I think you are looking for one of the following two expressions sum(unlist(BB)) sapply(BB, sum) On Mon, Apr 18, 2016 at 12:48 PM, Burhan ul haq <ulhaqz at gmail.com> wrote: > Hi, > > I request help with the following: > > INPUT: A data frame

... and here is a non-dplyr rsolution: > z <-gsub("[^[:digit:]]"," ",dd$Lower) > sapply(strsplit(z," +"),function(x)sum(as.numeric(x),na.rm=TRUE)) [1] 105 67 60 100 80 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom

Hi folks, I am confused whether the following is a bug or it is fine Here is the explanation a <- zoo(c(NA,1:9),1:10) Now If I do rollapply(a,FUN=mean,width=3,align="right") I get > rollapply(a,FUN=mean,width=3,align="right") 3 4 5 6 7 8 9 10 NA NA NA NA NA NA NA NA But I shouldn't be getting NA right ? i.e for index 10 I should get (1/3)*(9+8+7)

... and a slightly more efficient non-dplyr 1-liner: > sapply(strsplit(dd$Lower,"[^[:digit:]]"), function(x)sum(as.numeric(x), na.rm=TRUE)) [1] 105 67 60 100 80 Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On

Hi, I am having some trouble with the ClientAliveInterval server setting. My (C++) application fails to start an SSH channel to an OpensSSH server within this time-out period if it doesn't reply correctly to this 'keep-alive' no-op that is sent by the server. How is this no-op handled? I am using the libssh client library, and I could find no references on how to handle this.

Hi, I am currently setting up a backup script for the /home directory of a server. I send all the files on a remote machine through LAN connection using rsync to optimize bandwidth usage. The script is run as root on the server by a cron job but rsync connects to the remote machine as a normal user via an ssh key certificate. This leads to many "permission denied" errors, as the

Hello, I am attempting to "automate" a Bayesian normal linear regression using Zelig. Basically, I have a list containing several zelig() objects, each having a different formula, same data set, and same model (normal.bayes). My problem lies in the setx() method, where I am setting a numeric parameter to a value other than the mean. This is straightforward if I input the parameters

I've run an ordered logistic regression model in R with Zelig and am looking to calculate predicted probabilities. Zelig has a series of simple one line commands to generate the information I want on first differences and so forth. Unfortunately, I keep getting an error when running the zelig function and was wondering if there was a quick alternative for generating predicted probabilities for

Dear R users, I am trying to estimate to estimate the average treatmen effect on the treated (ATT) using first the MatchIt software to weight the data set and, after this, the Zelig software as shown in Ho et al. (2007). See here for an explanation of how to apply this technique in R: http://imai.princeton.edu/research/files/matchit.pdf I encounter a slight problem when I apply the weights that

Hi there, I'm wondering what Zelig in the following situation (code below) actually does. Is this considered as a so called regression adjustment after the propensity score matching? library(MatchIt) library(Zelig) data(lalonde) re78 represents the outcome variable 1. With Zelig m.out <- matchit(treat ~ age + educ + black + hispan + married + nodegree + re74 + re75, data = lalonde)

Dear all, Does anybody know why the following code returns an error message? >library(MatchIt) >library(Zelig) >data(lalonde) > >m.out1<-matchit(treat~age+educ+black+hispan+nodegree+married +re74+re75, method="full", data=lalonde) > >z.out1<-zelig(re78~age+educ+black+hispan+nodegree+married+re74+re75, data=match.data(m.out1, "control"),