similar to: Creating ordered colors for ordered factors

Dear R-List, I have a dataframe area<-c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10)) type<-c(rep(1:10,5)) a<-rnorm(50) b<-rnorm(50) c<-rnorm(50) d<-rnorm(50) df<-cbind(area,type,a,b,c,d) df area type a b c d [1,] 1 1 0.45608192 0.240378547 2.05208079 -1.18827462 [2,] 1 2 -0.12119506 -0.028078577

Help-Rs   As someone who is newer to R and trying to make the transition from Access into R, there is a frequetnly used function that I'd like to try and duplicate in the R world.  It involved creating an aggregate table of the top (n)  orders for an item by sum of cost over a select period of time.   So, take the following example :   group <- c(rep(1,10), rep(2,10), rep(3,10)) product

Hi R-helpers. #I start with the reproducible example: firm<-c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10)) year<-c(rep(1998:2007,5)) industry<-c(rep(1,20),rep(5,10),rep(7,10),rep(9,10)) X1<-rnorm(50) X2<-rnorm(50,mean=0.5,sd=0.1) Y<-rnorm(50,mean=0,sd=0.5) data<-data.frame(firm, industry,year,X1,X2,Y) data #I need to calculate for all the industries the following

I have a multiple text files, separated by a single space, that I need to combine into a single data.frame. Below is the track I'm on using list.files to capture the names of the files and then lapply with read.table. But I run into problems making a usable dataframe out of the data. #Creating example data in similar format to data I have sub <- rep(1,10) trial <- seq(1,10,1) size

Hi everyone! #I need a loop or a function that creates a X2 variable that is X1 without the extreme values (or X1 winsorized) by industry and year. #My reproducible example: firm<-sort(rep(1:1000,10),decreasing=F) year<-rep(1998:2007,1000) industry<-rep(c(rep(1,10),rep(2,10),rep(3,10),rep(4,10),rep(5,10),rep(6,10),rep(7,10),rep(8,10),rep(9,10), rep(10,10)),1000) X1<-rnorm(10000)

Full_Name: Bill Simpson Version: 65.1 OS: linux Submission from: (NULL) (193.62.250.209) Try this code as separate lines entered interactively, then try doit() doit<-function() { x<-seq(1,10) y1<-x+rnorm(10,1,1.5) y2<-x+rnorm(10,1,1) t.test(x,y1,paired=TRUE) t.test(x,y2,paired=TRUE) } doit() apparently executes only the last of a series of t.test()s. Maybe this is no bug,

Hi gues,   Is there any function in R for boxplot with different time points? t1 <- c(rep(1,20),rep(2,20)) t2 <- c(rep(1,10),rep(2,10),rep(1,10),rep(2,10)) x <- rnorm(40,5,1) dat <- data.frame(t1,t2,x) boxplot(x~t1,t2) Many thanks, Amor [[alternative HTML version deleted]]

Dear R users, I have two datasets: id1 <- c(rep(1,10), rep(2,10), rep(3,10)) value1 <- sample(1:100, 30, replace=TRUE) dataset1 <- cbind(id1,value1) id2 <- c(1,2,3) subtract.value <- c(1,3,5) dataset2 <- cbind(id2, subtract.value) I want to subtract the number of rows in the subtract.value that corresponds to the id value in dataset1. So for the 1 in id1, I want to

Hi guys, I'm very new to R and have been teaching myself over the past few months - it's a great tool and I'm hoping to use it to analyse my PhD data.As I'm a bit of a newb, I'd really appreciate any feedback and/or guidance with regards to the following questions that relate to generalized linearmixed modelling (or, at least, I think they do!)(if there is a 'better',

Dear Helpers, I wonder whether you might be able to help me. I have a plot composed of ggplot (and a follow on geom_smooth call). I would like to restrict the display range of the y axis to a smaller range, a sort of zooming onto a region. I attempted to use ylim, but it will effect the range (i.e. effect the geom_smooth call). Is there any way that I can save the results up to geom_smooth call

Hi I am writing a bunch of functions that take two, three or four arguments. These functions operate on vectors of the same length; but I want the function to behave sensibly if one or more arguments are scalars. "+" does this for two arguments: "+"(1:10,3) # interpreted as "+"(1:10,rep(3,10)) But my functions can take more arguments. Say f() takes three:

When I use the image() function for a relatively small matrix it works perfectly, eg.x <- 1:100 > z <- matrix(rnorm(10^4),10^2,10^2) > image(x=x,y=x,z=z,col=rainbow(3))but when I want to plot a larger matrix, it doesn't really work. Most of the times, it just plot a few intermitent points.x <- 1:1000 z <- matrix(rnorm(10^6),10^3,10^3) image(x=x,y=x,z=z,col=rainbow(3))

Hi, I have a dataframe containing data from individuals 1, ..., 12 (grouping variable "g" in the data frame below), which belong either to "A" or "B" (grouping variable "f"): set.seed(1) tmp <- data.frame(

Hi Group, I have a data frame below. Within this data frame there are samples (columns) that are measured more than once. Samples are indicated by "idx". So "id1" is present in columns 1, 3, and 5. Not every id is repeated. I would like to create a new data frame so that the repeated ids are averaged. For example, in the new data frame, columns 1, 3, and 5 of the original

hi, I want to add different colors on the background of a classical plot. Each color is associated to an interval of the x axis. example: the background is red on the interval [1,10], blue on [11,20]. I try the rect function but it isn't appropriate for the background. Can any one can help me please? best regards. --------------------------------- [[alternative

I would like to know if clogit function can be used as below clogit(group~., data=dataframe) When I try to use in above format it takes a long time, I would appreciate some pointers to get multiple combinations tested. set.seed(100) d=data.frame(x=rnorm(20)+5, x1=rnorm(20)+5, x2=rnorm(20)+5, x3=rnorm(20)+5, x4=rnorm(20)+5, x5=rnorm(20)+5, x6=rnorm(20)+5, x7=rnorm(20)+5, x8=rnorm(20)+5,

Full_Name: Raymond Salvador Version: R 1.6.2 OS: Windows ME Submission from: (NULL) (131.111.93.195) The mean function applied on individual components of several correlation matrices gives a wrong result (gives the first value instead of the mean). Here there is a simple example x1 <- rnorm(10,1,1) y1 <- rnorm(10,1,1) z1 <- cbind(x1,y1) w1 <- cor(z1) x2 <- rnorm(10,1,1) y2

Hello, I'd like to do something like: n<-100 zz<-cbind(rnorm(n),rnorm(n),floor(runif(n)*3+1)) colors<-c("red","green","blue") plot(zz,col=colors(zz[3])) and have a matrix of scatterplots colored by class. The above does not work, of course, but I'm not sure exactly what function I'm looking for. Thank you for your time, Dave, -- Dave

Dear R users, please can you help me understand the behaviour of abline using function lm. I'm trying to learn linearity over groups. So I make three groups with 10 values each: test=data.frame(cbind( l=c(rnorm(10,0,30),rnorm(10,100,30),rnorm(10,200,30)), t = c(rep(0,10), rep(1,10), rep(2,10)) )) when I do: plot(test$l~test$t) abline(lm(test$l~test$t)) the abline is a straight line

All, When specifying colors to xyplot w/ a groups argument, using auto.key no longer maintains the colors properly. I've searched the docs and help but haven't found exactly what I need ... I saw a few examples in the archives involving par.settings but that doesn't seem to do it. I also saw some people using key instead of auto.key, but that didn't seem consistent. Is there a