similar to: file.copy returning "FALSE"?

I'm trying to redirect where temporary files go under R to D:\temp\somerandomname from its default (C:\Documents and Settings\username\Temp\somerandomname) -- how do I go about doing this? --j -- Jonathan A. Greenberg, PhD Postdoctoral Scholar Center for Spatial Technologies and Remote Sensing (CSTARS) University of California, Davis One Shields Avenue The Barn, Room 250N Davis, CA 95616

R'ers: I was hoping I could get some direction on this. I have a dataset of the form: Y1,Y2,...,YM = f(X1,X2,...,XN), where N is >>> M The response data (Y1,Y2,...,YM) is frequency data, such that the sum of all Yi = 1.0. Both Xj and Yi are continuous variables. I'm trying to figure out the best approach(es) to solving for the model f() -- any ideas? I could solve

I have a numerical vector which contains a (poorly) formatted time column, which, in theory, should be HHMM, but was distributed as an integer, so, for 12:15 am, it is saved as "15" (e.g. HHMM = 0015 with the zeroes stripped). I'm trying to use this in conjunction with strptime, but I'm thinking because each time is an integer ranging from 1 to 4 digits, I probably need to

Our lab has a lot of different unix boxes, with different hardware, and I'm assuming (perhaps wrongly) that by setting a per-user package installation directory, the packages will only work on one type of hardware. Our systems are all set up to share the same home directory (and, thus, the same .Renviron file) -- so, is there a way to set, in the .Renviron file, per-computer or

Rers: I can't seem to locate the command to suppress what appears to be a faint internal grid when running the following command to make a filled contour plot of some data I have (x,y,z being the inputs):

Rers: I have some ecological data (stream velocity vs. % cover of submerged weeds) that shows strong evidence of a thresholding step-function, e.g. below some velocity, % cover ranges from 0% to 100% (with no apparent relationship to velocity within this range of velocities), but above a certain "threshold" velocity, the % cover does not appear to exceed, say, 10%. There are good

Quick question -- if I have a vector of strings that I'd like to split into two new vectors based on a substring that is inside of each string, what is the most efficient way to do this? The substring that I want to split on is multiple characters, if that matters, and it is contained in every element of the character vector. --j -- Jonathan A. Greenberg, PhD Postdoctoral Scholar

Rers: What is the preferred library/function for doing stratified random sampling from a dataset, given I want to control the number of samples (rather than the proportion of samples) per strata? Thanks! --j -- Jonathan A. Greenberg, PhD Postdoctoral Scholar Center for Spatial Technologies and Remote Sensing (CSTARS) University of California, Davis One Shields Avenue The Barn, Room

R-helpers: I'm working on an r-package that I want to make as easy-to-use as possible for a novice R-user, which includes automatically installing required packages. I, myself, am a novice R-packager, so the solution I came up with was to embed: print("Loading required packages...") if (!require("reshape")) { install.packages("reshape") } if

I've been playing with zoo a bit, and it seems ok except it doesn't support non-unique time stamps when performing joins. I have two databases which contain a dataframe of a Date object (with the time, not just MM/DD/YY), e.g.: DB 1: UniqueID,Date1,Data 1,Data 2 DB 2: Date2, Station, Data 3 We'll say Station can contain three values: A,B and C DB 1 may have some repeat times,

I'm hoping to get some "best practice" feedback for constructing a function call which takes an undefined set of DIFFERENT length vectors -- e.g. say we have two lists: list1=c(1:10) list2=c(2:4) lists = data.frame(list1,list2) coerces those two to be the same length (recycling list2 to fill in the missing rows) -- what is a quick way of having each of those lists retain their

Quick informal poll: what is everyone's favorite text editor for working with R? I'd like to hear from people who are using editors that have some level of direct R interface (e.g. Tinn-R, Komodo+SciViews). Thanks! --j -- Jonathan A. Greenberg, PhD Postdoctoral Scholar Center for Spatial Technologies and Remote Sensing (CSTARS) University of California, Davis One Shields Avenue The

I'm trying to figure out the best way to do a scatterplot using the following data as an example: plothelp_x=1:10 plothelp_A1=sin(plothelp_x) plothelp_A2=tan(plothelp_x) plothelp_B=c("A","B","C","A","B","C","A","B","C","A") (note that all 4 of these vectors have 10 entries each) What I would

(apologies for the cross-posting, and for this being a more general stats question rather than a specific-to-R one. I assure you I will be doing the actual analysis in R :) I am trying to determine the distribution and variance for a classic stochastic (transition) matrix problem such that: let x(t) be an initial state vector consisting of counts of classes A, B and C: x(t) =

R-helpers: I have a data frame containing 4 factor variables (let's say A,B,C, and D) and 1 numerical variable (N). I would like to produce a cross-tabulated data frame in which A,B,C are individual columns, each factor of D is its own column, and the field is calculated as a given function of N (I would like to have two output data frames, one with the mean(N) and one with the

I'm trying to hunt down an appropriate kriging package for my specific application, and I was hoping someone on the R list might have some pointers -- I'm interested in performing kriging and related spatial interpolations with one of the R packages, but I need to be able to provide my own point-to-point distances (e.g. I do not want to use standard between point distances, as calculated

Rhelpers: Having a problem solving this. I have an xyplot call that looks like this: print(xyplot(temp_species_EAM_Pred_Pop$x+temp_species_NULL_Pred_Pop$x~temp_species_EAM_Pred_Pop$Action,main=current_species, xlab="Action",ylab="Predicted Pop", xlim=c(xmin,xmax),ylim=c(ymin,ymax),

R-geographers... I'm trying to solve a problem to implement a line-by-line tiled processing using RGDAL (read 1 line of an image, process the one line, write one line of the image to a binary file). Everything except for the final step I'm able to do using a combination of RGDAL and r-base commands. Below is the basic structure, the input file "elev" can be any image file

I'm a bit confused why the following command is taking an extrodinarily long time (> 2-3 hours) to run on an 3.06ghz iMac (brand new). I'm trying to do a stratified random sample, drawing only a single value per UniqueID from the patch_summary data frame: uniqueids <- unique(patch_summary$UniqueID) uniqueids_stratasize <- c(1:length(uniqueids))*0+1

I'm trying to hunt down an appropriate kriging package for my specific application, and I was hoping someone on the R list might have some pointers -- I'm interested in performing kriging and related spatial interpolations with one of the R packages, but I need to be able to provide my own point-to-point distances (e.g. I do not want to use standard between point distances, as calculated