similar to: following Appendix A results in "plot.new has not been called yet"

Hello! I was reading R-intro and I have some suggestions: R-intro.html#A-sample-session rm(fm, fm1, lrf, x, dummy) suggestion rm(fm, fm1, lrf, x, y, w, dummy) The next section will look at data from the classical experiment of Michaelson and Morley to measure the speed of light. file.show("morley.tab") mm <- read.table("morley.tab") suggestion mm <- data(morley)

[For those on both this and samba-technical - sorry for the duplication. I meant to send this here, but I experienced a user error. :-) ] I'm having a problem related to the NT_STATUS_OBJECT_PATH_NOT_FOUND error and I am having a little difficulty discovering what this means. [root@monkey admin]# smbclient \\\\dapper\\dfs mypassword -U Myuser -E -W CISNET -D home\\staff\\fran -d0 -Tqca

I am doing very regular stuff like the following: attach(wtana) fm<- lm(Body.Wt.on.SD1~Heart.Wt, data=wtana) #fm<- lm(wtana$Body.Wt.on.SD1~wtana$Heart.Wt) lrf<- loess(Body.Wt.on.SD1~Heart.Wt, wtana) #lrf<- loess(wtana$Body.Wt.on.SD1~wtana$Heart.Wt) plot(Body.Wt.on.SD1,Heart.Wt) #plot(wtana$Body.Wt.on.SD1,wtana$Heart.Wt) #lines(spline(Heart.Wt,fitted(lrf)), col=2) abline(fm, col=4)

Dear all, I am running a mixed model using lmer. In order to obtain CI of individual coefficients I use mcmcsamp. However, I need advice which values that are most appropriate to present in result section of a paper. I have not used mixed models and lmer so much before so my question is probably very naive. However, to avoid to much problems with journal editors and referees addicted to

Hi List, I am new to this Rsoftware, i want to make a sereis for example which is having values like this, s<- 0,0.1,0.2,0.3,0.4........,1 i tryed this statement s<-0:0.1:1 but this giving an error megssage. but by default increment 1 it is taking ,,,,,so what to do ,, i want to use this varible in for loop.. like for(j in s) thanks in advance ANIL KUMAR( METEOROLOGIST) LRF

Dear R users, i am using locfit package developed by loader in R software, my problem is that as i am doing independont forecast using locfit object , i am able to do independont forecast for more than one years simultaniously. But when i am doing one year forecast(single) this code is giving following error... "Warning message: 'newdata' had 1 rows but variable(s) found have 24

Hi, List , i have 6 predictor variables and i want to make possible combinations of these 6 predictors ,all the data is in matrix form , if i am having 6 predictors than possible combination of sets are 64 2 power 6, or 63 ,whatever it may be i want to store the result in another variable to each combination and that i want to put in some model , i want to put every combination in some model

HI, List I want to know weather any body has used BMA Package for model averaging for prediction of future values.....What are the paprmeters we have to suplly to the model. Any script for the same. thanks in advance ANIL KUMAR( METEOROLOGIST) LRF SECTION NATIONAL CLIMATE CENTER ADGM(RESEARCH) INDIA METEOROLOGICAL DEPARTMENT SHIVIJI NAGAR PUNE-411005 INDIA MOBILE +919422023277

  Hello list, i have a very simple question about matrix assignment. i did like this. res<-1:30 dim(res)<-c(5,6) ind<-1:6 now i want to assign the value of this variable ind to first coloumn in matrix res. like res[,1]<-ind but this code is giving error , Actualy i have a for loop and value of ind variable is changing every time ,,total 6 times,,i want to assign every vlaue

&nbsp; Hi, List ,I am searching any package on R which can do wavelet filtering for mother wavelet morlet ,is anybody having any script for the same ? I am new to the RwAVELET ANALSSIS.. THANKS IN ADVANCE ANIL KUMAR ANIL KUMAR(&nbsp;METEOROLOGIST) LRF SECTION&nbsp; NATIONAL CLIMATE&nbsp;CENTER ADGM(RESEARCH) INDIA METEOROLOGICAL&nbsp;DEPARTMENT

Hi List, I have a time series of 122 values, actualy it is a time series of daily indian monsoon rainfall. now i want to filter this time series for a particular oscilation say 10 to 20days oscilation. i want to find out what amount of variance is explained by this mode. Which package is available in R for this purpose. and how to calculate nquest frequancy of this series. any help is much

HI LIST i am a new R user, i am trying to make a model,which will give me output in probability,which will take predictors and predictand serie as input and and give me output in terms of probability(e.g below normal,normal,above normal etc.).What is the package and what is the function for probability model.What are the possible methods for fitting such type of model,and what is the

Hi all, To follow up on an older thread, it was suggested that the following would produce confidence intervals for the estimated BLUPs from a linear mixed effect model: OrthoFem<-Orthodont[Orthodont$Sex=="Female",] fm1OrthF. <- lmer(distance~age+(age|Subject), data=OrthoFem) fm1.s <- coef(fm1OrthF.)$Subject fm1.s.var <- fm1OrthF. at bVar$Subject fm1.s0.s <-

I want to compute confidence intervals for the random effect estimates for each subject. From checking on postings, this is what I cobbled together using Orthodont data.frame as an example. There was some discussion of how to properly access lmer slots and bVar, but I'm not sure I understood. Is the approach shown below correct? Rick B. # Orthodont is from nlme (can't have both nlme and

Hi all, I am having issues comparing models with lmer. As an example, when I run the code below the model summaries (AIC, BIC, loglik) differ between the summary() and anova() commands. Can anyone clear up what's wrong? Thank you! Darren Ward library(lme4) data(sleepstudy) fm1<-lmer(Reaction ~ Days + (1|Subject), sleepstudy) summary(fm1) fm2<-lmer(Reaction ~ Days +

How does one coerce predict.gls to incorporate the fitted correlation structure from the gls object into predictions? In the example below the AR(1) process with phi=0.545 is not used with predict.gls. Is there another function that does this? I'm going to want to fit a few dozen models varying in order from AR(1) to AR(3) and would like to look at the fits with the correlation structure

Dear R-Helpers, I was calling the TukeyHSD function and not getting confidence intervals or p-values. It turns out this was caused by missing data and the fact that I had previously turned on R Commander (Rcmdr). John Fox knew that Rcmdr sets na.action to na.exclude, which causes the problem. If you have this problem, you can either exit Rcmdr before calling TukeyHSD or you can set na.action to

Hello: I am trying to understand why glm() does not replicate the results in Dobson, "Introduction to Generalized Linear Models," pp. 17-20. I set up the following model. The variable CONDT is assumed as Poisson and the objective is to estimate the expected value. The data (chronic medical conditions among women in Australia) is as follows: CONDT <- c(0, 1, 1, 0, 2, 3, 0, 1,

Hi Folks, I'm trying to understand the model specification formalities for 'lme', and the documentation is leaving me a bit confused. Specifically, using the example dataset 'Orthodont' in the 'nlme' package, first I use the invocation given in the example shown by "?lme": > fm1 <- lme(distance ~ age, data = Orthodont) # random is ~ age Despite the

Hey Folks: New to R and learning as I go, but really, I know just enough to get myself into trouble. I've waded through everything up till now, and don't see anything in the search that is directly helpful for the POS that I've created. The GOAL: All I want in the world is a program that performs 1-way ANOVA's on every column in a data set (taking the first column as the