similar to: recode Variable in dependence of values of two other variables

Hi R users, I'm kind stuck in my R experience... I want to have a multiple barchart with n windows, but with the same background for each window, and I want that background to be a recorded dotplot. First, is it possible ? If so, I guess I have to call a record plot in the panel function but how ? As there is no panel.plot and I can't use the recorded plot as an argument for the

hi all why does the following not work??? this was someone elses code and i couldnt explain why it doesn't work. m=matrix(c(0,0),2,1) v=matrix(c(1,0,0,1),2,2) Y=function(X1,X2,mu=m,V=v) { X=matrix(c(X1,X2),2,1) a=(1/((2*pi)*sqrt(det(V))))*exp((-0.5)*(t(X-mu)%*%solve(V)%*%(X-mu))) a[1] } x1=seq(-1,1) x2=x1 Z=outer(x1,x2,FUN="Y",mu=m,V=v) persp(x1,x2,Z) my code:

Hello, I want to plot several lines to a main plot but at the end of each loop, it erases the last one. Here my program: alpha<-5 beta<-10 var<-0.5 s<-runif(1000,0,50) m<-length(s) variancealpha<-0.002 variancebeta<-0.051 variancevar<-0.001 alphachap<-vector() betachap<-vector() varchap<-vector() epsilon<-vector() b<-vector()

I want to implement the following algorithm in R: I want to split my data, use a t test to compare both means of the groups to see if they significantly differ from each other. If this is a yes (p < alpha) I want to split again (into 4 groups) and do the same procedure twice, and stop otherwise (here the problem arises). As a final result I would have different groups of data. I made some

Assuming a data frame or matrix with two columns representing variable that you want to aggregate over. you want to calculate column means, by year, for each Id example<-data.frame(id=c(rep(12345,5),rep(54321,6),rep(45678,7)),Year=rep(seq(1900,1902,by=1),6), x=seq(1,18,by=1),y=seq(18,1,by=-1)) example id Year x y 1 12345 1900 1 18 2 12345 1901 2 17 3 12345 1902 3 16 4 12345

Hi here is the code as example lars is in package lars > x<-matrix(rnorm(20*5,0,1),20,5) > bs<-matrix(sample(seq(1:10),5),5,1) > er<-rnorm(20,0,1) > y<-x%*%bs+er > lobj<-lars(x,y,type="lasso") > names(lobj) [1] "call" "type" "df" "lambda" "R2" [6] "RSS"

Hi, I have numerical variable that I want to recode into categories '0' and '1 and more' and do analysis with that data. I have tried various of possibilities to do so, but I am sucked and nothing is working. recode(Q12, "0='A';1:30='B'") cut(Q12, breaks=c(0,1,30), lables=c('0', '1 and more')) cat(Q12, "0=0;1-33=1") What should

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I know this comes up, but I didn't see my exact issue in the archives. I have variables in a dataframe that need to be recoded. Here is what I'm dealing with I have a factor called aa > class(aa) [1] "factor" > table(aa) aa * 0 1 2 3 A B C D L N T 0 0 1908 725 2089 0 0 67 0 0 2 1 6 I need to recode

Dear Rusers, My question is about "recode variables". First, i'd like to say something about the idea of recoding: My dataset have three variables:type,soiltem and airtem,which means grass type, soil temperature and air temperature. As we all known, the change of air temperature is greater than soil temperature,so the values in those two different temperaturemay represent different

Hi, Is there an efficient way recoding variables in a data.frame using base R? My purpose is to create new variables and attach them into old data.frame. The basic idea is shown below, but how to create recoding for A, B and C and assing them into new variables? df <- data.frame(A = c(1:5), B = c(3,6,2,8,10), C = c(0,15,5,9,12)) df$A[df$A <= 3] <- "x" df$A[df$A > 3 &

Hi Experts, I am new to R, and was wondering how to do 3D linear regression in R. In other words, I need to Fit a 3-Dimensional Line to Data Points (input). I googled before posting this, and found that it is possible in Matlab and other commercial packages. For example, see the Matlab link:

Greetings, I'm in the painful process of migrating from SAS to R. In the process I've discovered that there are some basic things that I am getting hung up on. The most basic is the simple recoding of variables. Suppose I create a vector x <- rnorm(10000) and I want to recode all values of x > 1.5 to NA. How would I do that in R? TIA Cheers, Patrick

I am just beginning to use Sweave with Lyx on a Mac (R2.8.1). I have 12 chunks of Sweave code that work fine, but this piece: <<>>= library(car)

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Dear R-List, I would like to recode categorial variables into binary data, so that all values above median are coded 1 and all values below 0, separating each var into two equally large groups (e.g. good performers = 0 vs. bad performers =1). I have not succeeded so far in finding a nice solution to do that in R. I thought there might be a better way than ordering each column and recoding the

Hi all I am trying to do a simple recode which I am stumbling on. I figure there must be any easy way but haven't come across it. Given data of A","B","C","D","E","A" it would be nice to recode this into say three categories ie A and B becomes "Treat1", C becomes "Treat 2" and E becomes "Treat 3". I tried

I am hoping for some advice regarding the difficulties I have been having recoding variables which are contained in a csv file. Table 1 (below) shows there are two types of blanks - as reported in the first two columns. I am using windows XP & the latets version of R. When blanks cells are replaced with a value of n using syntax: > affect [affect==""] <- "n" there

Thanks to the R creators for such a great statistical system. Thanks to the R help list, I have (finally) gotten far enough in R to have a question I hope to be worth posting. I'm using the recode function from John Fox's car package and have encountered some unexpected behavior. Consider the following example: ## Begin cut-and-paste example require( car ) set.seed(12345) nn <-

Hello, we have 80 text files with matrices. Each matrix represents a map (rows for latitude and columns for longitude), the 80 maps represent steps in time. In addition, we have a vector x of length 80. We would like to compute a regression between matrices (response through time) and x and create maps representing coefficients, r2 etc. Problem: the 80 matrices are of the size 4000 x 3500 and we