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Hi everyone, I've got a question concerning the function acf(.) in R for calculating the autocorrelation in my data. I have a table with daily returns of several stocks over time and I would like to calculate the autocorrelation for all the series (not only for one time series). How can I do this? After that I want to apply an autoregressive model based on the estimated lag in the

I want to sample within groups, and when a group has only one associated number to just return that number. If I use this code: groups <- c(1, 2, 2, 2, 3) numbers <- 1:5 tapply(numbers, groups, FUN = sample) I get the following output: > groups <- c(1, 2, 2, 2, 3) > numbers <- 1:5 > tapply(numbers, groups, FUN = sample) $`1` [1] 1 $`2` [1] 3 2 4 $`3` [1] 2 3 5 1 4

...-problem-tp3830284p3836422.html > Sent from the R help mailing list archive at Nabble.com. > > > > ------------------------------ > > Message: 2 > Date: Fri, 23 Sep 2011 13:07:57 +0200 > From: "Helios de Rosario"<helios.derosario at ibv.upv.es> > To:<jcbouette at gmail.com> > Cc: r-help at r-project.org > Subject: Re: [R] How make a x,y dataset from a formula based entry > Message-ID:<4E7C84AD0200000C0000A9F8 at mailhost.biomec.upv.es> > Content-Type: text/plain; charset=UTF-8 > > To separate the parts of a formula, use as.cha...

Hello all, So I am using the (formula entry) method for randomForests: randomForest(y~x1+x2+...+x39+x40,data=xxx,...) but the issue is that some of the items in that package dont take a formula entry - you have to explicitly state the y and x vector: randomForest(x=xxx[,c('x1','x2',...,'x40')],y=xxx[,'y'],...) Now my question is whether there is a function/way

I have a matrix called mat and y is the column number of my response and x is a vector of the column numbers of my terms. The variable name of y can change, so I don't want to hardcode it. I can find out the name as follows: > names(mat)[y] [1] "er12.l" Then I can run the regression by hard coding the variable name as follows: > mod <-

Dear list, I just tried to do the same thing, and did not find anything on a weighted qqplot. My weights are actually counts (positive integers). Here is a modification of qqplot, following Duncan Murdoch's suggestion. Any feedback would be welcome! Thanks, Jean-Christophe weighted.qqplot <- function (x, y, plot.it = TRUE, xlab = deparse(substitute(x)), ylab = deparse(substitute(y)),