similar to: concatenating two vectors

I have a data frame in wide format that I'd like to convert to long format. For example, in wide format I have: id A1B1 A1B2 A2B1 A2B2 1 1 400 475 420 510 2 2 390 500 470 472 3 3 428 512 555 610 4 4 703 787 801 822 5 5 611 634 721 705 6 6 543 522 612 788 7 7 411 488 506 623 8 8 654 644 711 795 A is one repeated-measures variable with levels 1 and 2. B is a second repeated-measures variable

I have design with two repeated-measures factor, and no grouping factor. I can analyze the dataset successfully in other software, including my legacy DOS version BMDP, and R's 'aov' function. I would like to use 'Anova' in 'car' in order to obtain the sphericity tests and the H-F corrected p-values. I do not believe the data are truly deficient in rank. I

To whom it may concern I made some analysis with R using the command Anova. However, I found some problmes with the output obtained by selecting type II o type III sum of squares. Briefly, I have to do a 2x3 mixed model anova, wherein the first factor is a between factor and the second factor is a within factor. I use the command Anova in the list below, because I want to obtain also the sum

Hi, I have a vector of strings like: c("a1b1","a2b2","a1b2") which I want to spilt into two parts like: c("a1","a2","a2") and c("b1","b2,"b2"). So there is always a first part with a+number and a second part with b+number. Unfortunately there is no separator I could use to directly split the vectors.. Any idea

Hi folks, Suppose I have a series of cases each with categorical factors A, B. What is the best way to "glue" A and B together into a single factor? For example, given A0 B1 ... A1 B1 ... A0 B2 ... A1 B0 ... A0 B0 ... A1 B2 ... then I'd like to end up with a single factor with levels A0B0, A0B1, A0B2, A1B0, A1B1, A1B2 according to all the combinations which actually occur in

Hi all, In preparation for teaching a class next week, I've been reviewing R's standard modelling algebra. I've used it for a long time and have a pretty good intuitive feel for how it works, but would like to understand more of the technical details. The best (online) reference I've found so far is the section in "An Introduction to R"

Dear all, I want to manipulate a character string such as ex<-"cbind(data$response1,data$response2)" in R in two ways: 1) extracting the "response1" portion of ex 2) replacing "$" with "." I am wondering that is it possible efficiently doing these in R? Best Ozgur -- View this message in context:

Dear all, Actually I could not decide who to contact, then decided to post here. If not appropriate sorry for that. I have written some functions in R which might be supposed to available in the base package but not available. I am wondering that how can I submit those functions to that package? Best Ozgur ----- ************************************ Ozgur ASAR Research Assistant Middle East

Hello, I have a dataframe (Lx) with 5 Lb, and 5 Lw variables. I want to create several variables according to the loop presented below (data attached). Lx <- read.csv("Lx.csv", header=T, sep=",") for (i in 1:20) { Lx$sb1[i] <- Lx$Lb1[i+1]/Lx$Lb1[i] Lx$sb2[i] <- Lx$Lb2[i+1]/Lx$Lb2[i] Lx$sb3[i] <- Lx$Lb3[i+1]/Lx$Lb3[i] Lx$sb4[i] <-

Hi, Your mistake seems to be in sum(v[1:x]) You create "x" as a vector but your treat it as a single number. v[1:x] expects "x" to be a single number and only considers its first element which is 1. If I understand your query correctly, the following might handle your problem: sum.vec <-NULL for (x in 1:1000){ t <- rbinom(1000, 1, 0.5) v <- replace(t,t==0,-1)

Dear R users, I'd like to remove some descriptions when I use "filter". > filter(1:10, rep(1, 3)) Time Series: Start = 1 End = 10 Frequency = 1 [1] NA 6 9 12 15 18 21 24 27 NA That is, I want only this [1] NA 6 9 12 15 18 21 24 27 NA Thank you in advance. Kathie -- View this message in context:

Hello R-Experts, I am facing the problem that I have to estimate several parameters for a lot of different dependent variables. One single regression looks something like this: y = beta0 + beta1 * x1 + beta2 * x2 + beta3 * x1 * x2 + beta4 * x4 + beta5 * lag(x4,-1) where y is the dependent variable and xi are the independent ones. Important to me are the different estimates of betai and their

Hi Do I have to load/download the whole package over and over again everytime when I use the R-Project? It often prompt me the error message "could not find function"- but I'm rather sure I have used the function before so I'm not entirely sure it couldn't find it again when I shut down the computer or so. Is it to do with directory or clashing with other software? Any

Dear all, I have some trouble with special characters while building my R package. I tried to follow the usual LATEX format, but could not fix the problem: For instance, for "greater than or equal", I tried "\geq", but R says that this is an unknown macro. Could anyone direct me how to solve this issue? Best Ozgur ----- ************************************ Ozgur ASAR

Hi group, I've been thinking of calculating euclidean distance between each column of a data frames that each consists of standardized numerical columns. However, I don't know if there's a way of summarizing the overall distance by some kind of metrics. If anyone know a proper way of doing so and/or a package I would greatly appreciate your suggestions. Thanks very much! Kel --

hello, I try to run simulation of levene's test to find the p-value but the error of replacement has length zero occur, could anyone help me to fix this problem? asim <- 1000 pv<-rep(NA,asim) for(i in 1:asim) {print(i) set.seed(i) g1 <- rnorm(20,0,2) g2 <- rnorm(20,0,2) g3 <- rnorm(20,0,2) x <- c(g1,g2,g3) group<-as.factor(c(rep(1,20),rep(2,20),rep(3,20))) library(Rcmdr)

Dear list users, I have a data frame as below specified. From the 1st of May to the 30th of September of several years (e.g. from 2004 to 2011) I have a frequency of accidents. I need the mean of accidents divided by weeks (i.e. the mean of accidents from the 1st to the 7th of May of all the years, from the 8th to the 14th of May, ..., from the 29th to the 31st of May, from the 1st to the 7th of

I am wondering how to obtain SE estimates for fixed effects from a nonlinear mixed effects model? I have fixed effects corresponding to three factors A, B and C with 2, 3 and 3 levels respectively. I have fit a model of the following general form: nlme1<-nlme(y~ SasympOrig(x, Asym, lrc), data=df, fixed=list(Asym~A*B*C, lrc~A*B*C), start=c(fixef(ETR.nlme)[1], rep(0,17), fixef(ETR.nlme)[2],

Hello, I''m trying to create a HVM virtual machine (windows guest) with 3G of memory but this isn''t working. Xen create the domain but nothing happens (the OS don''t start and the cpu time remains 0). Things start to work with 2000MB or below. Is there some kind of upper limit for HVM virtual machines? I''m using a Dell PowerEdge 8250 machine with 16GB of memory.

Dear Researchers, I am looking for to read a SAS macro in R. Although I searched it on web, I couldn’t find anything. Can you help me or direct me? Thank you for your interest and patience. Best. Ozgur [[alternative HTML version deleted]]