search for: stephenb

I am trying to load a dll compiled with the latest cygwin into R 2.7.0 R version 2.7.0 (2008-04-22) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 I have: Sys.getenv("Path") Path

I am trying to load a dll compiled with the latest cygwin into R 2.7.0 R version 2.7.0 (2008-04-22) Copyright (C) 2008 The R Foundation for Statistical Computing ISBN 3-900051-07-0 I have: Sys.getenv("Path") Path

is there a way to label points in a graph using text(locator(1),"text") after ggplot() or qplot() ? > qplot(date, psavert, data = economics, geom = "line",main="jhdjd")->p > p+opts(text(locator(1),"HHHH"),new=T) does not work. -- View this message in context: http://www.nabble.com/text%28%29-to-label-points-in-ggplot-tp23545135p23545135.html Sent

R version 2.15.0 (2012-03-30) Copyright (C) 2012 The R Foundation for Statistical Computing ISBN 3-900051-07-0 Platform: i386-pc-mingw32/i386 (32-bit) package ?survey? successfully unpacked and MD5 sums checked package ?odfWeave.survey? successfully unpacked and MD5 sums checked > library(odfWeave.survey) Loading required package: odfWeave Error: package ?odfWeave? could not be loaded any

Greetings, I am new to R and have some background knowledge about SQL. I'd like to know whether there is a way to manipulate the R datasets (or data frames) using SQL statements. For example, I have two data frames and both of them have a column called "id", then I want to join this two data frames into one. In SQL, we can just simply use the join comment. What should we do in R?

Hello everybody, Data is myd <- data.frame(id1=rep(c("a","b","c"),each=3),id2=rep(1:3,3),val=rnorm(9)) I want to get a cumulative sum over each of id1. trying aggregate does not work myd$pcum <- aggregate(myd[,c("val")],list(orig=myd$id1),cumsum) Please suggest a solution. In real the dataframe is huge so looping with for and subsetting is not a

I am using an example posted in this help forum to work with a file. the head of the file looks like: 988887 2007-03-05 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 0 0 988887 2007-03-06 2007-06-01 90 3 5.450 205500.00 999.00 999.000 0.000 1 0 988887 2007-03-07 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100 2 0 988887 2007-03-08 2007-06-01 90 3 5.450 205500.00 999.00 999.000 -0.100

Hi group, I found a module for adaptive kernel density estimation for Stata users, but unfortunetly I don't have access to Stata, can I find a similar approach using R? Thank u so much 4 ur time. [[alternative HTML version deleted]]

I am trying to analyse some data and was given R code to do this with but there seem to be errors in the code. My level of knowledge is improving but still limited. The details are; Data on clover lines; Lines.txt attached. Comma seperations Code: options(digits=3) clover <- read.table("Lines.txt",header=T,sep=",") vnames <- names(clover);nv <- length(vnames)