similar to: CCF and Lag questions

Hi, I am using R 1.9.1 on on i686 PC with SuSE Linux 9.0. I have a data.frame, e.g.: > myData <- data.frame( var1 = c( 1:4 ), var2 = c (5:8 ) ) If I add a new column by > myData$var3 <- myData[ , "var1" ] + myData[ , "var2" ] everything is fine, but if I omit the commas: > myData$var4 <- myData[ "var1" ] + myData[ "var2" ] the name

-- Eredeti üzenet -- Feladó: Dévaványai Agamemnón &lt;devavanyai@citromail.hu&gt;Címzett: r-hel@r-project.org, r-hel@r-project.orgElküldve: 2010. július 29. 16:29Tárgy : duplicates Sorry! I try it again Dear R Users! I have a dataframe with duplicatecases. Var1 duplicated by var2. var1 var2 var3 var4 var5 1 4 500 1 2 1 3 200 2 5 1

Dear R Users! I have a dataframe with duplicate cases. Var1 duplicated by var2. var1 var2 var3 var4 var5 var6 1 4 500 1 2 a 1 3 200 2 5 b 1 8 125 1 9 b

Sorry! I try it again Dear R Users! I have a dataframe with duplicatecases. Var1 duplicated by var2. var1 var2 var3 var4 var5 1 4 500 1 2 1 3 200 2 5 1 8 125 1 9 2 2 120 2 52 2 6 22 1 20 2 9 400 1 22 3 1 100 2 8 3 2 200 5 40 4

Hi R-experts I have many text files to read and combined them into one into R that are output from other programs. My textfile have unbalanced number of rows for example: ;this is example ; r help Var1 Var2 Var3 Var4 Var5 0 0.05 0.01 12 1 0.04 0.06 18 A 2 0.05 0.08 14 3 0.01 0.06

Hi R users, I have a question about plotting. The following two datasets are an example. What I have in mind is like the attached figure, but just have two rows, top row is for DF1, bottom row is for DF2. The top and bottom rows, have x-axis as var1, var2, var3, etc, while the y-axis represents A. For each row, only the leftmost panel has y-axis ticks and label. For the two rows, only the bottom

Hi, what is the recommended way to vertically concatenate 2 data frames with the same column names but different number of rows? My problem is something along these lines: df1 <- data.frame(var1=var1,var2=var2,var3=var3) # nrow(df1)=1000 df2 <- data.frame(var1=var4,var2=var5,var3=var6) # nrow(df2)=2000 I tried df <- c(df1,df2), no success. stack does not seem to be appropriate

Dear all, I am trying (!!!) to generate pdfs that have 8 plots on one page: df = data.frame( day = c(1,2,3,4), var1 = c(1,2,3,4), var2 = c(100,200,300,4000), var3 = c(10,20,300,40000), var4 = c(100000,20000,30000,4000), var5 = c(10,20,30,40), var6 = c(0.001,0.002,0.003,0.004), var7 = c(123,223,123,412), var8 = c(213,123,234,435), all = as.factor(c(1,1,1,1)))

Dear everyone, I have looked all over the internet but I cannot find a way to solve my problem. In my data I want to sum a couple of variables. Some of these variables have NA values, and when I add them together, the result is NA dat <- data.frame( id = gl(5,1), var1 = rnorm(5, 10), var2 = rnorm(5, 7), var3 = rnorm(5, 6), var4 = rnorm(5, 3), var5 = rnorm(5, 8) ) dat[3,3] <- NA dat[4,5]

Dear All Sorry for this simple question, I could not solve it by spending days. My data looks like this: # data set.seed(1234) clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100 level for this factor var; yvar <- rnorm(40, 10,6); var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2); var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15,

Dear all, I have a dataset that looks like id var1 var2 var4 var7 var8 1 0.0 0.1 0.3 0.9 0.0 2 0.4 0.6 0.0 0.0 0.2 3 0.0 0.0 0.0 0.8 0.7 Some columns are missed, for example, here the fourth (var3), sixth(var5) and seventh (var6) columns. I want to first determine which columns are missed in a huge dataset and then add the missed

Dear R users, I'm new but already fascinated R user so please forgive for my ignorance. I have the problem, I read most of help pages but couldn't find the solution. The problem follows.... I have large data set 10,000 rows and more than 100 columns... Say something like var1,var2,var2,var4.......var120 ------------------------------------------- 12,12,345,657,67,8.....

Dear list, after fitting an lrm with the Design package (stored as "mymodel") I try running a summary, but I get the following error: dim(mydata) [1] 235 9 names(mydata) [1] "id" "VAR1" "VAR2" "VAR3" "VAR4" "VAR5" "VAR6" "VAR7" "VAR8" summary(mymodel) Error in `contrasts<-`(`*tmp*`,

Hello! I have a data set: set.seed(123) y<-data.frame(week=seq(as.Date("2010-01-03"), as.Date("2011-01-31"),by="week")) y$var1<-c(1,2,3,round(rnorm(54),1)) y$var2<-c(10,20,30,round(rnorm(54),1)) # All I need is to create lagged variables for var1 and var2. I looked around a bit and found several ways of doing it. They all seem quite complicated - while in

Hi, I am trying to merge data similar to the example data below > dat0 id var1 var2 var3 2 1 0 1 3 1 0 1 4 0 1 1 5 0 1 1 > dat1 id var4 var5 var6 2 1 0 1 3 1 0 1 6 0 1 1 7 0 1 1 > dat2 id

Hello I carried out a logistic regression and found predicted values. Then I want to see both predictors (var1,var2..) and predicted values in same matrix. In other words, I need to know each combinations and predicted values. I used: cbind(var1,var2,var3,var4,predict(glm.obj,type="resp")) I got a somewhat strange result: var1 var2 var3 var4 var5 var6 predicted vals ------

Dear R users, I need help with translating these SAS codes into R with lme()? I have a longitudinal data with repeated measures (measurements are equally spaced in time, subjects are measured several times a year). I need to allow slope and intercept vary. SAS codes are: proc mixed data = survey method=reml; class subject var1 var3 var2 time; model score = var2 score_base var4 var5 var3

Hi, is there a possibilty to get my function output with "cat " as data.frame.rows with variables ? Var1---------------- 8 15 1 3 Var2---------------- 0.170 0.319 0.0213 0.0638 Var3---------------- 83.8 88.6 90 75 Var4---------------- 84.3 84.3 100 83.3 Var5---------------- 62.5 56 20 53.3 function(data.frame) { .... ....

Hi, [some background] I have a dataset which describes a number of subjects doing a "scientific discovery". That is, they have to discover the rules underlying a particular domain. To do so, they have to set the levels of 5 variables which leads to a certain outcome. To identify what kind of "experiments" the subjects did, I want to combine these levels into one variable

Dear List, I have Multi-level Data i= Indivitual Level g= Group Level var1= First Variable of interest var2= Second Variable of interest and I want to count the frequency of "var1" and "var2" on the group level. I found a way, but there must be a much simpler way. data.ml <- data.frame(i=c(1:8),g=as.factor(c(1,1,1,2,2,3,3,3)),var1=c(3,3,3,4,4,4,4 ,4),