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Dear R users, how do I e.g. square each second element of a vector with an even number of elements? Or more generally to apply a function to every 'nth' element of a vector. I looked into the apply functions, but found no hint. For example: v <- c(1, 2, 3, 4) mysquare <- function (x) { return (x*x) } w <- applyfun(v, mysquare, 2) then w should be c(1, 4, 3, 16) Thanks for

Dear R users, Given this data: x <- seq(1,100,1) dx <- as.POSIXct(x*900, origin="2007-06-01 00:00:00") dfx <- data.frame(dx) Now to play around for example: subset(dfx, dx > as.POSIXct("2007-06-01 16:00:00")) Ok. Now for some reason I want to extract the datapoints between hours 10:00:00 and 14:00:00, so I thought well: subset(dfx, dx >

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",

Dear All, I was wondering why the forecast for an additive HoltWinters model is given by Yhat[t+h] = a[t] + h * b[t] + s[t + 1 + (h - 1) mod p]. I am a student and new to time series analysis and forecasting. That said, I considered t = 13 and h = 1: Yhat[13+1] = a[13] + b[13] + s[13 + 1] It seems odd that to predict Yhat[14], you would need a s[14] which in turn depends on Y[14], given that

Dear R Users, I am doing stats::decompose() on 4 different time series. When I issue csdA <- decompose(tsA) plot(csdA) I get a summary plot for observed, trend, seasonal and random components of decomposed time series tsA. As I understand it, the object returned by decompose() has it's own plot method where mfrow(4,1) etc. is defined. Now suppose I wanted to wrap those mfrow(4,1) into

Hello Everyone, I am using R ver. 2.10.1 (2009-12-14). I installed lattice today via install.packages. I am doing this minimal example: M = read.csv("/path/to/csv") cloud(x ~ y * z, data = M) this correctly gives me a scatterplot of the csv data which has 3 columns. Every column contains 1800 numeric 0 < values < 1300 when I want to plot the corresponding wireframe via

Hi there, I was doing great with R, ggplot and tikzDevice, when suddenly it stopped working. I can do a plot just fine on the R online graphics device. I can also open a tikzdevice via tikz(). However, the plot (both ggplot and R graphics plot) call leads to the error: "createLockFile(lockname): cannot create lock file" I see that this is related to my OS, namely Ubuntu 10.04. I

Hello Everyone, the basic idea is to generate an initial (MS Word) report by R (plots, tables and outline structure), pass this document around so everyone can add / change content (except plots and tables) and later to be able to update the R plot / table logic and update the already modified word file. I was toying around with the R2wd [1] package to test whether it is a viable way of writing

Dear R Users and Developers, I am trying to do the equivalent of v <- c(1,2,3,3,2,1,) vu <- unique(v) for a vector such as v2 <- c(1.02, 2.03, 1.00, 3.04, 3.06) vut <- ... As indicated in the subject, we need approximately unique values with a defined tolerance, i.e. for the v2 vector the resulting vut vector using a tolerance of .1 should return e.g. [1] 1.02 2.03 3.06 Also,

Dear R Developers, DISCLAIMER: I am new to package development in R and new to this list. I am trying to do something along the lines of: SEXP test_fun (SEXP filename) { const char *inputfile = translateChar(STRING_ELT(filename, 0)); int abc = some_function(inputfile); ... } The code compiles fine, but I get a warning: "passing argument of 'some_function' discards qualifiers

Dear R users, I want to do a fitted.contour plot of selected columns of a dataframe M with M$AM and M$Irradiance as x and y axes respectively. The level of the contour shall be determined by M$PR. Some words on my data first. Dataframe M looks like: head(M$Irradiance) [1] 293 350 412 419 477 509 head(M$AM) [1] 2.407 2.161 1.964 1.805 1.673 1.563 head(M$PR) [1] 70.102 72.600 75.097 80.167

Dear R Users, Lets assume I have this data frame: x y z 1 1.00 5 0.5 2 1.02 5 0.7 3 1.04 7 0.1 4 1.06 9 0.4 x and y columns are sorted and the values not necessarily integers. z values are not sorted. Now I would like to create a matrix out of this with x as first column values and y as first row values. Matrix element a_11 shall be left NA. The a_ij should have the z value for the