similar to: gam confidence interval (package mgcv)

Dear R-helpers, when I have an R code chunk in a sweave file like this: <<>>= x <- 1:10 # this comment disapears x # this one does not! print(x) #mean mean(x) @ The first comment does not appear in the sweaved document, the second one does. How can this be? I have tried print=TRUE and keep.source=TRUE, but neither seem to affect this behavior. thanks, Remko

Dear R-helpers, can I use a POSIXct date as the x variable in interpSpline? The help page says x and y need to be numeric... is there a workaround? example: library(splines) testdfr <- data.frame(Date=seq(as.POSIXct("2008-08-01"),as.POSIXct("2008-09-01"), length=10)) testdfr$yvar <- rnorm(10) sp <- interpSpline(yvar ~ Date, testdfr) preddfr <-

Dear list, I am trying to use RGoogleDocs, but I am connecting through a proxy server. I know RCurl is used for the connection, which should be able to deal with proxies and such. How do I set this up for RCurl? And can I use those settings with RGoogleDocs as well? I have the name of the proxy server and the port number. (Windows XP). thanks, Remko

Dear R-helpers, thanks for yesterday's speeding-up tip. Here is my next query: I have lots of polygons (not necessarily convex ones, and they never have holes) given by x,y coordinates. I want to get the polygon that is the union of these polygons. This is my current method, but I am hoping there is a faster method (up to thousands of polygons, each with ca. 40 xy points). Example:

Dear R-helpers, making a package (windowsXP), that includes a bunch of functions, but none have examples (all example code is within \dontrun{} blocks). I do R CMD check Maeswrap, all bits get OK-ed, except: "Running examples in 'Maeswrap-Ex.R' failed." When I run the 'Maeswrap-Ex.R' file myself, there are no problems. Any pointers? thanks Remko

Hi all, I am having some problems calling a python script from R that resides in a folder that is in the path (WindowsXP): > system("quickPadTool.py") Warning message: In system("quickPadTool.py") : quickPadTool.py not found # I also tried 'shell' (and shell.exec as well). > shell("quickPadTool.py") 'quickPadTool.py' is not recognized as an

Dear R-helpers, I am looking for an implementation of the box-counting algorithm to estimate the box dimension of a cloud of points in 3D (aka fractal dimension, or similarity dimension). The package 'fdim' might be doing this, but the documentation is awful and I don't understand what is what there. Does anyone know of an implementation of this algorithm in R, or elsewhere, or

Dear R-helpers, I have a problem converting an object made with the 'chron' function to a POSIXct object: # Make date based on DOY dat <- chron(dates=232, origin.=c(month=1, day=1, year=2008)) dat #[1] 08/20/08 # Converting to POSIXct uses current timezone (Sydney): as.POSIXct(dat) #[1] "2008-08-20 10:00:00 EST" # Setting GMT timezone has no effect? as.POSIXct(dat,

Dear R-helpers, I tried to build a DLL like I have done so many times, but this time on my new machine, but it gives the erorr: (from cmd window) >R CMD SHLIB Boxcnt.f MAKE Version 5.2 Copyright (c) 1987, 2000 Borland Error c:/PROGRA~1/R/R-210~1.1/share/make/winshlib.mk 4: Command syntax error *** 1 errors during make *** The error is not in my Fortran file, because I also tried other files

Dear R-helpers, apologies if this is somewhere in a manual, I have not been able to find anything relevant. I run Windows Vista. I have some Fortran code in a subroutine, and have no problem calling this from R with .Fortran, compiling the code either with 'R CMD SHLIB' or independently with gfortran. But is it possible to have more than one subroutine in my source file, one depending

Dear R-helpers, I have a fresh installation of windows vista, and R 2.12.0 (session info below). Problem: > require(sp) Loading required package: sp Error in library.dynam(lib, package, package.lib) : DLL 'lattice' not found: maybe not installed for this architecture? > require(lattice) Loading required package: lattice Failed with error: ?package 'lattice' is not

length(unique(c(1,2,2)))==length(c(1,2,2)) I use the above test to test if all the elements in a vector are unique. But I'm wondering if there is a convenient function to do so in R library.

Dear R-helpers, an rgl-ers in particular, what is the easiest way to plot a section of a plane in 3D, that is given by the xyz coordinates of the outline? Suppose I have a polygon - which I know for sure is a set of coordinates on the same plane. One method I found is to use surf.tri from the geometry package, and then plot the triangles with rgl.triangles. This method is not perfect though,

Dear R-helpers, I have a function that adds some segments to the current plot, but if I the current plot is made with any of the lattice functions (in my case, levelplot), I should use lsegments rather than segments. How can I tell if the current device was made with plot() or e.g. levelplot() or another lattice function? dev.cur() does not help me, it just tells me "windows 2".

Hi, Time for another of my "newbie" questions. Is it possible to build up a data.frame "row by row" as I go I'm going to be running a bunch of experiments (many in a loop) to test different things. I'm using AUC as my main performance measure. My thought was to add a row to a data.frame for each iteration and then have a nice summary report at the end. I found

It seems that an vector or other non elemental data type can not be assigned to an element in the data.frame. I'm wondering what is the walk around. > li=data.frame(a=c(0,1), b=c('x','y')) > li$b[[1]]= 'x' > li$b[[2]]<- c('y','z') Error in li$b[[2]] <- c("y", "z") : more elements supplied than there are to replace

Hi all, I am using ACS micro data (PUMS) with one of the columns as a factor for the place of birth (POBPF). I would like to create a column (POBR) containing a rank corresponding to the place of the observation in the POBPF rankings. For example, if a person is from Oregon, Oregon is the most popular Place of Birth, so each person who came from Oregon should have a 1 in their POBR.

I've built a package that contains only two functions for a test run. They are: g <- function(x){ x <- x^2 class(x) <- "foo" x } print.foo <- function(x, ...){ cat("This is a test:\n") cat(x, "\n") invisible(x) } Simply testing these functions in the R workspace prior to a build yields: > g(1:5) This is a test: 1 4 9 16 25 Now, I

I'm looking for goodness of fit tests for gamma distributions with large data sizes. I have a matrix with around 10,000 data values in it and i have fitted a gamma distribution over a histogram of the data. The problem is testing how well that distribution fits. Chi-squared seems to be used more for discrete distributions and kolmogorov-smirnov seems that large sample sizes make it had to

I have a set of labels arranged along a timeframe in a. Each label has a timestamp and marks a state until the next label. The dataframe a contains 5 such timestamps and 5 associated labels. This means, on a continious scale between 1-100, there are 5 markers. E.g. 'abc' marks the timestampls between 10 and 19, 'def' marks the timestamps between 20 and 32, and so on. a <-