similar to: Odd behaviour with scale()

Please consider a data frame A B C D 1 4 5 0 2 3 2 75 3 4 1 84 4 5 1 90 5 3 0 100 Is there a way to plot column B and C as barplot *and* D as line on the same graph?? R-2.0.1 powered by Mandrake 10.1 ------------------------------------------------------------------------------------------------------------------------- Landini dr. Massimiliano Tel. mob. (+39) 347 140 11 94 Tel./Fax. (+39)

Hello, can anyone tell me if R has any special function for simulating the structure of human populations? Something like the genetic algorithm? I need to simulate a sample of a population with a specific structure. Is there something on R that can help me? Thanks to everyone. __________________________________________________________

Dear all, I have several questions regarding fisher.test() in R, and I'd highly appreciate any help with it. I have a group of observations, each having people's income, and an indicator of whether selected in or out a program. I want to test the difference between income of people who are in and out. Because the distribution is far from normal, I decide to use the fisher's exact

Dear all, I have several questions regarding fisher.test() in R, and I'd highly appreciate any help with it. I have a group of observations, each having people's income, and an indicator of whether selected in or out a program. I want to test the difference between income of people who are in and out. Because the distribution is far from normal, I decide to use the fisher's exact

Hi, I wonder if anyone has written any code to implement the suggestions of Smart et al (2004) in the Bulletin of the Ecological Society of America for a new way of graphically presenting the results of logistic regression (see www.esapubs.org/bulletin/backissues/085-3/bulletinjuly2004_2column.htm#t ools1 for the full text)? I couldn't find anything relating to this sort of graphical

This is slightly off-topic, but there was a discussion about MCMC a couple of weeks ago. OpenBUGS can operate from R, at least in Windows (there are some problems in Linux at the moment). The interface with R is one are that there are plans to work on: it's a bit basic at the moment. Bob -- Bob O'Hara Dept. of Mathematics and Statistics P.O. Box 68 (Gustaf H??llstr??min katu 2b)

I'm sure I'm missing something obvious here, but I can't find the solution (including in the FAQ etc.). I have a vector of names of variables like this: NRes.x.y. where x and y are numbers. I want to extract these numbers as numbers to use elsewhere. I can extract the numbers as a list of characters using strsplit(), and convert that to a data frame, e.g.:

I can only assume I'm betraying my ignorance here, but this is not what I would expect. I'm getting the following from a stepwise selection (with both step and stepAIC): > step(lm(sqrt(Grids)~ SE + Edge + NH), scope=~ (Edge + SE + NH)^2) Start: AIC= 593.56 sqrt(Grids) ~ SE + Edge + NH Df Sum of Sq RSS AIC <none> 2147.0 593.6 + Edge:NH 1

I have a simple (!) problem. What I want to do is to create a legend with Greek letters, and substituting numbers into the legend. Like this: mu=1:3 Mean=rep(mu, each=20) plot(runif(60), rnorm(60,Mean,0.1), pch=Mean) # create a plot legend(0.6,1.7, paste("mu =", 1:3), pch=mu) but with a Greek letter mu. I think the solution has something to do with substitute() possibly along with

Anybody know where I can get the Pinheiro/Bates book? I can't find a bookstore w/ stock and the publisher says they don't know when they'll have it again. Thanks. -Frank

Hi! I was trying to implement a probit model on a dichotomous outcome variable and found that the predictions were outside the (0,1) interval that one should get. I later tried it with some simulated data with a similar result. Here is a toy program I wrote and I cant figure why I should be getting such odd predictions. x1<-rnorm(1000) x2<-rnorm(1000) x3<-rnorm(1000)

4000:6000 gives you 4000, 4001, ..., 6000. I suspect you want population= c(seq(4000, 6000, length=5), seq(3500, 4300, length=5), seq(3000, 3200, length=5)) Bob On 20 September 2017 at 17:07, Shivi Bhatia <shivipmp82 at gmail.com> wrote: > Hi Team, > > I using the syntax as: > > data.df<- data.frame( > city= c(rep(c("Delhi",

Hi Team, I using the syntax as: data.df<- data.frame( city= c(rep(c("Delhi", "Bangalore","Chandigarh"),each=5)), population= c(4000:6000,3500:4300,3000:3200) ) But i am getting the error as arguments imply differing number of rows: 15, 3003. Tried searching google but could not understand & find the solution. Thanks, Shivi [[alternative HTML version

Hello, i am a newby on R and i am trying to make a backward selection on a binomial-logit glm on a large dataset (69000 lines for 145 predictors). After 3 days working, the stepAIC function did not terminate. I do not know if that is normal but i would like to try computing a "homemade" backward with a repeated glm ; at each step, the predictor with the max pvalue would be

The loop never assigns anything to d0, only t. The first line makes t a character string "d0$V1" (or "d0$V2" etc.). The second line assigns either 0 or 1 to t. Looking at this, I don't think you've got into the R psychology (bad news if you want to use R, good news in many other ways). I assume d0 is a list, so could you put the V's into a vector, and then just use

It might help if you provided the code you used. It's possible that you didn't use direction="backward" in stepAIC(). Or if you did, it was still running, so whatever else you try will still be slow. The statement "R provides only the pvalues for each level" is wrong: look at the anova() function. Bob On 29 June 2017 at 11:13, Beno?t PELE <benoit.pele at

I've got a colleague who's using a GLMM to analyse her data, and I've told her that she needs to include an offset. However, glmmPQL doesn't seem to allow one to be included. Is there anyway of doing this? Bob -- Bob O'Hara Rolf Nevanlinna Institute P.O. Box 4 (Yliopistonkatu 5) FIN-00014 University of Helsinki Finland Telephone: +358-9-191 23743 Mobile: +358 50 599

I try to do a test for dirichlet process for Multivariate normal, but Winbugs always says "expected multivariate node", does that mean I miss something at initialization? I will really appreciate the help to solve this problem Here is the R code, and Winbugs code. model { for(i in 1:N){ y[i,1:2] ~ dmnorm(mu[i,],tau[i,,]) S[i] ~ dcat(pi[]) mu[i,1:2] <- mu.star[S[i],]

Hi. I am new here, and I am writing this Winbugs code with BRugs. n=length(bi.bmi) Lagegp=13 Lgen=2 Lrace=5 Lstra=15 Lpsu=2 #model gen x race bi.bmi.model=function(){ # likelihood for (i in 1:n){ bi.bmi[i]~ dbern(p[i]) logit(p[i])<- a0 + a1[agegp[i]]+a2[gen[i]]+a3[race[i]] + a12[agegp[i], gen[i]] + gam[stra[i]]+ u[psu[i],stra[i]] } # constraints for a1, a2, a3, a12 a1[1]<-0.0

Dear All, I have a question regarding predict.rpart. I use rpart to build classification and regression trees and I deal with data with relatively large number of input variables (predictors). For example, I build an rpart model like this rpartModel <- rpart(Y ~ X, method="class", minsplit =1, minbucket=nMinBucket,cp=nCp); and get predictors used in building the model like