similar to: How to speed up regressions (related to data.frame)

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 <-

I have a character string and I would like to remove the leading and tailing white spaces. The example for 'sub' shows how to remove the trailing white spaces, but I still can't figure out how to remove both trailing and leading white spaces because I can't find any documentation for what "+$" means or what "\\s+$" means. Maybe its because I don't have a

I created a small example to show something that I do a lot of. "scale" data by month and return a data.frame with the output. "id" represents repeated observations over "time" and I want to scale the "slope" variable. The "out" variable shows the output I want. My for..loop does the job but is probably very slow versus other methods. ddply

Can anyone tell me how to get R to include a double quote in the middle of a character string? For example, the following code is close: > fnd<-"Open fnd 'test'" > cat(fnd) Open fnd 'test'> > But instead of Open fnd 'test' I need: Open fnd "test". Difference seems minor, but I am writing batch files for another

I am completely new to LaTeX and Sweave, so I am trying to follow the tutorial in the following link: http://www.r-bloggers.com/using-latex-r-and-sweave-to-create-reports-in- windows/ I installed MiKTeX 2.9 and TeXnicCenter, but I get a build error when compiler the example file: The two errors are: "Error: running 'texi2dvi' on 'test.tex' failed" and "R> !

I am trying to create plots within a for loop and output them to a pdf. Here is a working example using plot: gg <- data.frame(datadate=1:4, spread=5:8) pdf() for (i in 1:3) { plot(gg$datadate, gg$spread, main=i) } dev.off() I am trying to learn more about ggplot2 so I try a slight modification and it doesn't work. Anyone

I am using Sweave to generate a document in which ggplot2 figures are embedded. I am using the following code in a particular plot within a subfloat environment: <<qplotARbosreg, echo = FALSE, fig = TRUE>>= print(qplot(bosday2, Arday2, data= arbostimearonlyNArm, colour=factor(bos2), shape=factor(bos2), size=factor(cumARscore), position="jitter", main="Days to BOS by

All, I am not understanding the scoping used in foreach when it is used inside a function. I keep getting "could not find function" errors for functions that are in memory when I try to use foreach within a function call. I have a simple example below. "testFun" is in memory and works when called by foreach directly, but when I place foreach in a function called

I would like to learn how to parse a mixed text/xml document I downloaded from the sec.gov website (see example below). I would like to parse this to get the value for each xml tag and then access it within R, but I don't know much about xml so I don't even know where to start debugging the errors I am getting in this example code. Can anyone help me get started? Thanks, Roger ftp

I modified an example in the object.size help page to create a function I want to be able to run: "mysize" <- function() { z <- sapply(ls(), function(w) object.size(get(w))) as.matrix(rev(sort(z))[1:5]) } mysize() When I test the lines inside the function it works fine: > z <- sapply(ls(), function(w) object.size(get(w))) > as.matrix(rev(sort(z))[1:5])

Can anyone comment or point me to a discussion of the pros and cons of robust regressions, vs. a more "manual" approach to trimming outliers and/or "normalizing" data used in regression analysis?

All, I have managed to download files from web sites and ftp sites using R, so just for fun I tried to do so from the SEC's ftp site using the following code: ftp <- "ftp://anonymous:test at ftp.sec.gov/edgar/full-index/company.idx" download.file(url=ftp, destfile="test.txt") And it does not work. R says it cannot open the URL. If I paste the ftp part into IE it

Apologies for a naive question: Can R be installed and run on a server (operating system Windows Server 2008)? Thank you! -- Dimitri Liakhovitski

All, I have a variable called `go` and it has a single quote in the name column of line 47 that I am trying to get rid of. I have tried using gsub, but I cannot get the syntax correct to tell R to remove the ' (single quote). > go[47,] gvkey Symbol Name Rank MarketCap MemoDate Action Analyst Reason SharesHeld 75 065105 BJ BJ'S WHOLESALE CLUB INC 0.9579

Dear Group, I am having trouble with using rlm on multivariate data sets. When I call rlm I get Error in lm.wfit(x, y, w, method = "qr") : incompatible dimensions lm on the same data sets seem to work well (see code example). Am I doing something wrong? I have already browsed through the forums and google but could not find any related discussions. I use Windows XP and R

Dear R-devel, There seems to be a discrepancy in the order in which lm and rlm evaluate their arguments. This causes rlm to sometimes produce an error where lm is just fine. Here is a little script that illustrate the issue: > library(MASS) > ## create data > n <- 100 > dat <- data.frame(x=rep(c(-1,0,1), n), y=rnorm(3*n)) > > ## call lm, works fine > summary(lm(y ~

Dear List, I used rlm to calculate two regression models for two data sets (rlm due to two outlying values in one of the data sets). Now I want to compare the two regression slopes. I came across some R-code of Spencer Graves in reply to a similar problem: http://www.mail-archive.com/r-help at stat.math.ethz.ch/msg06666.html The code was: > df1 <- data.frame(x=1:10, y=1:10+rnorm(10))

Quantstrat useRs, I have a number of questions about how to use quantstrat that I have accumulated since I have begun playing with it. First, can the orderqty be dynamic? All of the examples I have seen are based on placing an order for 100 shares when a rule is triggered. Is it possible to set it up to buy the maximum number of shares given the starting or current equity? Similar to that

On Thu, 16 Sep 2004, RenE J.V. Bertin wrote: > Dear all, > > A few quick questions about interpreting and evaluating the results of > linear regressions, to which I hope equally quick answers are possible. > > 1) The summary.lm method prints the R and R^2 correlation coefficients > (something reviewers like to see). It works on glm objects and (after > tweaking it to

Hei Group, I want to compare the relative importance of predictors in a multiple linear regression y~a+bx1+cx2... However, bptest indicates heteroskedasticity of my model. I therefore perform a robust regression (rlm), in combination with bootstrapping (as outlined in J. Fox, Bootstrapping Regression Models). Now I want to compare the relative importance of my predictors. Can I rely on the