similar to: question on xyplot

Platform: WIN2000 Version of R: 1.6.2 I'm interested in plotting fitted values in a trellis xyplot. I believe the following should work; however, I only get the points (not the fitted lines). library(lattice) trellis.device(bg="white") xyplot(MULTDV~TIME|SUBNUM,data=TEMP, panel=function(x,y){ panel.xyplot(x,y) lines(x,fitted(lm(y~poly(x,1),na.action=na.omit)))

Hello all: I've read the document named "A Brief Introduction to R, the multilevel package and the nlme package". At p68, one can transform the dataset to the required format by using "make.univ". I wanna know,how the new variable "MULTDV" is calculated(can you show me the formula if possible please?)?And what's the usage of this new variable in the following

The as.matrix function behaves in a puzzling manner. The help file says: "`as.matrix' is a generic function. The method for data frames will convert any non-numeric column into a character vector using `format' and so return a character matrix." But this does not appear to be the case in the following example. Instead, as.matrix turns a data.frame into a list, not a

Hi list, Using the lmList function from ?nlme package? I get the following error message: ?Error in !unlist(lapply(sum.lst, is.null)) : invalid argument type? # this is the syntax used # fm_cream <-lmList(MULTDV~TIME|cod, data=zz, na.action=na.omit) # summary(fm_cream) When I generate a simple example the function works, but on the real data I get that message. I imagine that it is a

Hello, I am a newbie to the lattice package in R, and I'm trying to make a plot using the xyplot function. I have repeated measures data (2 conditions) for two different groups of subjects (teens and adults). So far, I've made a basic graph using xyplot(y ~x, group=subnum, data=mydata, type="b"). Now I would like to make all the teens' lines one color and the adults'

Hello R-users, Checking the archives, I recently came across this topic: "export tables to Excel files" (http://r.789695.n4.nabble.com/export-tables-to-Excel-files-td1565679.html#a1565679), and the following interesting references have been proposed: http://rwiki.sciviews.org/doku.php?id=tips:data-io:ms_windows

Hi R users! I am trying to learn some multilevel analysis, but unfortunately i am now very confused. The reason: http://www.ats.ucla.edu/stat/hlm/seminars/hlm_mlm/mlm_hlm_seminar.htm http://www.ats.ucla.edu/stat/sas/seminars/sas_mlm/mlm_sas_seminar.htm and MlmSoftRev. pdf from mlmRev package. >From what i see, the first two links seem to declare the level one variable as a random part (i

i'm sorry. i had an error in my previous code because i left out a letter in the rownames. while fixing that, i also found a solution. so i'm sorry for the confusion. below is my fix. temp2 <- matrix(rnorm(10),nc=1,nrow=10) rownames(temp2) <-

this is a bad question but I can't figure it out and i've tried. if i sort the 2 column matrix , temp1, by the first column, then things work as expected. But, if I sort the 1 column matrix, temp2, then it gets turned coerced to a vector. I realize that I need to use drop=FALSE but i've put it in a few different places with no success. Thanks. temp1 <-

R-help - I have this set of aggregated tables (sample data below via dput()). And I would like to have delayValue as the column variables with the "temp" (temp1, temp2, temp3) values as the row variables. However I would like to have the temp variables *aggregated into single rows* so that I have the frequency ("Freq" | counts) of each time each "delayValue" occurs

Hi, I use sapply very frequently, but I have recently noticed a behavior of sapply which I don't understand and have never seen before. Basically, sapply returns what looks like a matrix, says it a matrix, and appears to let me do matrix things (like transpose). But it is also a list and behaves like a list when I subset it, not a vector (so I can't sort a row for instance). I

Dear all, As part of a larger function, I am randomly removing rows from a data frame. The number of removed rows is determmined by a Poisson distribution with a low mean. Sometimes, the random number is 0, and that's when the problem starts: My data frame: > temp occ x y dbh age 801 0 2977.196 3090.225 6 36.0 802 0 2951.892 3083.769 8 40.6 803 0 2919.111

I am using R 2.1.1 in an windows XP environment. I have 2 dataframes, temp1 and temp2. Each dataframe has 20 variables (“cocolumns") and 525 observations (“rows”). All variables are numeric. I want to create a new dataframe that also has 20 columns and 525 rows. The values in this dataframe should be the sum of the 2 other dataframe. (i.e. temp1$column

hi, i have a list of data.frame that has same structure. i would like to know a efficient way of rbind-ing it. right now, i write: n = length(temp) # 'temp' is a list of data.frames temp2 = data.frame() for (i in 1:n) temp2 = rbind( temp2, temp[[i]]) return(temp2) but this is not an efficient way since we keeping overwriting temp2. i wonder if there's faster way. thanks --

Hi, I am a new novice of LLVM, and I want know how to get the left-hand operand of an instruction? For example: how to get the %temp2 operand in the next instruction: %temp2 = malloc i8, i32 %n Thanks a lot! Best Regards! -------------- next part -------------- An HTML attachment was scrubbed... URL:

Hi, I have following kind of model : Y = X1 * a1 + X2 * a2 + error Here sampled data for Y, X1, X2 are like that : Y <- replicate(10, matrix(rnorm(2),2), simplify = F) X1 <- replicate(10, matrix(rnorm(4),2), simplify = F) X2 <- replicate(10, matrix(rnorm(4),2), simplify = F) My goal is to calculate LS estimates of vectors "a1" and "a2". Can anyone please guide me

Hi R users I want to use the lme package for a multilevel analysis on the following example: > math<-c(2, 3,2, 5, 6 ,7 , 7) > sex<-c(1, 2, 1, 2, 2, 2, 1) > school_A<-c(1,1,1,2,2,2,2) > school_B<-c(10,10,10,20,20,20,20) > mydata<-data.frame(math, sex, school_A, school_B) > mydata School_A and school_B are two different school characteristics, math is an

Okay, someone explain this behaviour to me: Browse[1]> replace(rep(0, 4000), temp1[12] , temp2[12])[3925] [1] 0.4462404 Browse[1]> temp1[12] [1] 3926 Browse[1]> temp2[12] [1] 0.4462404 Browse[1]> replace(rep(0, 4000), 3926 , temp2[12])[3925] [1] 0 For some reason, R seems to shift indices along when doing this replacement. Has anyone encountered this bug before? It seems to crop up

I think need to do something like this: dat<-data.frame(state=sample(id=rep(1:5,each=200),1:3, 1000, replace=T,prob=c(0.7,0.05,0.25)),V1=runif(1,10,1000),V2=rnorm(1000)) rle.dat<-rle(dat$state) temp<-1 out<-data.frame(id=1:length(rle.dat$length)) for(i in 1:length(rle.dat$length)){ temp2<-temp+rle.dat$length[[i]] out$V1[i]<-mean(dat$V1[temp:temp2])

Hi R-users,   I intend to apply a mixed model on a set of longitudinal data, with a negative binomial distributed dependent variable, and after following the discussions on R help list I saw that more experienced people recommended using lmer (from lme4 pack), glmmPQL (from MASS) or glmm.admb (from glmmADMB pack)     My first problem: yesterday this syntax was ok, now I get this weird message (I