similar to: Scoping issue?

>I have a series of write statements because >i am writing to a file >where the characters strings are the column names of a dataframe >and the numbers are the elements in a particular row. >So, a file might look like > >AAA 2.1 >BB 3.1 >AHLZ 0.2 > >and it would be named "rowname".mls. > >so, each time i get to a new row, i create a new file and

Hello, I'm using a very large data set (n > 100,000 for 7 columns), for which I'm pretty happy dealing with pairwise-deleted correlations to populate my correlation table. E.g., a <- cor(cbind(col1, col2, col3),use="pairwise.complete.obs") ...however, I am interested in the number of cases used to compute each cell of the correlation table. I am unable to find such a

I await Luke''s node settings implementation with interest. At the moment however, I have this sort of ugliness: $site = $hostname ? { fred => "opsera", barney => "bedrock", default => "unknown site", ... } So I''ve knocked up this little function to use CSV files instead. Now I can just do: $site =

Hi all, This is a very basic question, but I just can't figure out why R is handling a loop I'm writing the way it is. Here is the script I have written: grid_2_series<-function(gage_handle,data_type,filename) series_name<-paste(gage_handle,data_type,sep="_") data_grid<-read.table(file=paste(filename,".txt",sep=""))

Hi list, Could you explain the error I see here? Thanks! ## I'm using R 2.8.0 on WinXP, Hmisc_3.4-3 > table1 <- matrix(10, 180,7) > cell.format <- matrix("", ncol=7, nrow=180) > cell.format[c(seq(3,180,6),seq(4,180,6)),] <- "color{red}" > cell.format[c(seq(5,180,6),seq(6,180,6)),] <- "color{green}" > > latex(table1,

Hello Lets say as an example I have a dataframe with the following attributes: rownum(1:405), colnum(1:287), year(2000:2009), daily(rownum x colnum x year) and foragePotential (0:1, by 0.01). The data is actually stored in a netcdf file and I'm trying to provide a conceptual version of the data. Ok. I need to calculate a moving mean and a moving variance for each cell on the following

Dear R gurus, I have the following code, but I still not know how to estimate and extract confidence intervals (95%CI) from resampling. Thanks! ~Adriana #data penta<-c(770,729,640,486,450,410,400,340,306,283,278,260,253,242,240,229,201,198,190,186,180,170,168,151,150,148,147,125,117,110,107,104,85,83,80,74,70,66,54,46,45,43,40,38,10) x<-log(penta+1) plot(ecdf(x),

Simple problem but I don't see the answer. I'm trying to clean up some data I have 120 columns in a data.frame. I have one value in a column named "blaw" that I want to change. How do I find the coordinates. I can find the row by doing a subset on the data.frame but how do I find out here "blaw " is in columns without manually counting them or converting names(Df) to a

Full_Name: Gregory R. Warnes Version: 1.2.0, 1.2.3 OS: SunOS gsun124 5.8 Generic_108528-03 sun4u sparc SUNW,Ultra-5_10 Submission from: (NULL) (12.18.36.49) When using expand.model.frame on a model that specifies a subset selection, an error is generated on the variable used for the subset selection. Example: > data <- data.frame(x=1:10,y=1:10,z=1:10,m=1:10) > model <- lm( y ~

> Thanks. This is also present in the current pre-1.3.0. Your patch > looks correct, but I wonder if the default for "enclos" > should not be > environment(formula(model)) rather than parent.frame() as it is now? > > (And wouldn't it be better named "envir"?) Peter, I was merely making an incremental improvement, your suggestions provide

Does R, or will R, be integrating the changes to the Chambers/Lucent S language under their version 5.0? If not already, then when? John Thaden Little Rock, Arkansas, USA -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read http://www.ci.tuwien.ac.at/~hornik/R/R-FAQ.html Send "info", "help", or "[un]subscribe"

Dear R-Help list: I'm using the Matrix library to operate on 600 X ~5000 element unsymmetrical sparse arrays. So far, so good, but if I find I need more speed or functionality, how hard would it be to utilize other sparse matrix toolsets from within R, say MUMPS, PARDISO or UMFPACK, that do not have explicit R interfaces? More information on these is available here

The generic rule is that R is not a macro language, so looping of names of things gets awkward. It is usually easier to use compound objects like lists and iterate over them. E.g. datanames <- paste0("aa_", 2000:2007) datalist <- lapply(datanames, get) names(datalist) <- datanames col1 <- lapply(datalist, "[[", 1) colnum <- lapply(col1, as.numeric) (The 2nd

This shouldn't be hard, but it's just not coming to me: Given a vector, e.g., v <- c(20, 134, 45, 20, 24, 500, 20, 20, 20) how can I get the index of the last value in the vector having a value greater than n, in this case, greater than 20? I'm looking for an efficient function I can use on very large matrices, as the FUN argument in the apply() command. Confidentiality

R pattern-matching and replacement functions are vectorized: they can operate on vectors of targets. However, they can only use one pattern and replacement. Here is code to apply a different pattern and replacement for every target. My question: can it be done better? sub2 <- function(pattern, replacement, x) { len <- length(x) if (length(pattern) == 1) pattern <-

Hi! Thanks for the replies! I understand people more accustomed to R doesn't like looping much, and that thinking about loops is something I do since I worked with Stata a lot. The syntax from Peter Dalgaard was really clever, and I learned a lot from it, even though it didn't solve my problem (I guess it wasn't very well explained). My problem was basically that I have a data matrix

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

In the Matrix package v. 0.995-11 I see that the dgTMatrix Class for compressed, sparse, triplet-form matrices handles Identically indexed data instances by summing their values, e.g., library(Matrix) (Mt <- new("dgTMatrix", i = as.integer(c(0,0,1,1,4)), j = as.integer(c(0,1,2,2,4)), x = as.double(1:5), Dim = as.integer(c(5,5)))) ## 5 x 5 sparse Matrix of class

Dear R list members, I'm encountering a problem with expand.model.frame(): Suppose that I define the following simple function (meant just to illustrate the problem): > fun <- function(model){ + expand.model.frame(model, all.vars(formula(model))) + } > and I have the following model, created with an explicit data argument: > mod Call:

I am pretty pleased with baselines I fit to chromatograms using the runquantile() function in caTools(v1.6) when its probs parameter is set to 0.2 and its k parameter to ~1/20th of n (e.g., k ~ 225 for n ~ 4500, where n is time series length). This ignores occasional low- side outliers, and, after baseline subtraction, I can re-adjust any negative values to zero. But runquantile's