similar to: CHM help does not find help docs in package stats

Dear all, I want to get a series of boxplots (grouped by two factors) and I want to overlay the original observations and the following code does almost what I want: library(ggplot) ddf <- data.frame(x=factor(rep(LETTERS[1:4], each=30)), y = runif(120,0,10), grp = factor(rep(rep(1:3, 10), 4))) ggplot(ddf, aes(x, y, colour=grp)) + geom_boxplot() + geom_point() Yet the position of the points

Dear all, I want to use aggregate.formula to conveniently summarize a data.frame. I have quiet some variables in the data.frame and thus I don't want to write all these names by hand, but instead create them on the fly. This approach has the advantage that if there will be even more columns in the data.frame I don't have to change the code. I've hence tried to construct a formula

Dear all, In a function I paste a string and convert it to a formula which I pass to lm[e]. The idea is to write a function which takes the name of the response variable and the explanatory variable and the data frame as an argument and calculates an lm[e]. (see example below) This works fine, but if I want to make a prediction on this model, R complains that the object holding the formula

Hi everybody, Is there a particular reason, why this code does not work as intended: z <- factor(LETTERS[1:3], ordered = TRUE) u <- 4:6 min(z[u > 4]) Error in Summary.factor(2:3, na.rm = FALSE) : min not meaningful for factors I agree that min is indeed not meaningful for not ordered factors, but it makes sense for ordered factors. Especially since z[3] <

Dear all, Assume that I have the following data structure: d <- expand.grid(subj=1:5, time=1:3, treatment=LETTERS[1:3]) d$value <- 10 ^ (as.numeric(d$treatment) + 1) + 10 * d$subj + d$time d$value2 <- 100000 + d$value where d$treatment == "C" stands for my control group. What I want to achieve now is to subtract the values corresponding to d$treatment == "C" from

Dear all, I produced the following graph with ggplot which is almost fine, yet I don't like that the legend for "Means" and "Observations" includes a line, though no line is used in the plot for those two (the line for "Overall Mean" on the other hand is wanted): library(ggplot2) ddf <- data.frame(x = factor(rep(LETTERS[1:2], 5)), y = rnorm(10)) p <-

Hi everybody, I'd like to have a list with two elements, where both elements have the same value: z <- list(a=1, b=1) If it happens, that I've to change the value, I've to assure that I change both. This is error prone. Hence, a better way to achieve this is to define: tmp <- 1 z <- list(a=tmp, b=tmp) Now, I'm wondering if it is possible to make this more compact: z

Hi everybody, I want an x-axis which has xlim=c(max, min) rather than xlim=c(min, max) in order to reflect the type of the process (cooling): library(lattice) myprepanel <- function(x,y,...) list(xlim=rev(range(x))) x <- rep(1:10, 100) z <- factor(sample(10, 1000, T)) y <- rnorm(1000, x, as.numeric(z)) xyplot(y~x|z, scales=list(x="free"), prepanel=myprepanel) This works

Dear all, Today I figured out that there is a neat function called droplevels, which, well, drops unused levels in a data frame. I tried the function with some of my data sets and it turned out that not only the unused levels were dropped but also the contrasts I set via "C". I had a look into the code, and this behaviour arises from the fact that droplevels uses simply factor to drop

Hi all, In R it is possible to sum tables: > (a <- table(rep(1:3, sample(10,3)))) 1 2 3 2 5 7 > a+a 1 2 3 4 10 14 Now suppose that I have a list of tables, where each table counts the same things > k <- list(a,a,a) How can I sum all tables in k? > do.call(sum, k) [1] 42 does not work since it sums over each table. > do.call(`+`, list(a,a)) 1 2 3 4 10

Hi everybody, how is it possible to refer to an argument passed to a function in the function call? What I like to do, is something like f <- function(x,y) x+y f(2, x) # should give 4 The problem is of course that x is only known inside the function. Of course I could specify something like f(z<-2,z) but I'm just curious whether it is possible to use a fancy combination of eval,

High everybody, currently I'm writinig a package that, for a given family of variance functions depending on a parameter theta, say, computes the extended quasi likelihood (eql) function for different values of theta. The computation involves a couple of calls of the 'glm' routine. What I'm doing now is to call 'lapply' for a list of theta values and a function, that

Dear all, Is there a reason, why there is no +-operator for aes (i.e. uneval) objects (as there is for themes and gg objects)? I had a couple of cases where such an operator would be useful, for instance to combine the result of aes and aes_string in functions. Any flaws with the following proposition: `+.uneval` <- function(e1, e2) { dup <- names(e1) %in% names(e2) if (any(dup)) {

Hello everybody, Currently I'm developing a library, which uses some functions from another package (namely plotrix). Consequently, I listed this dependency in the DESCRIPTION file. When I try to run "R CMD check mypackage", the check fails, for the library plotrix cannot be found on the system. As far as I understood "R CMD check" uses --vanilla implicitly, thus, no

Dear all, I am developing a package, which bundles my most frequently used functions. One of those is a modified version of droplevels from the base package (basically, it preserves any contrast function which was used to create the factor, contrast matrices are not kept, for they could be wrong if a level is dropped). In my NAMESPACE file I've the following directives, which should export

Dear all, How can I make an index plot with lattice, that is plotting a vector simply against its particular index in the vector, i.e. something similar to y <- rnorm(10) plot(y) I don't want to specify the x's manually, as this could become cumbersome when having multiple panels. I tried something like library(lattice) mp <- function(x, y, ...) { x <- 1:length(y)

Hi all, Suppose we have the following matrix m <- matrix(c(1,2,3,2,1,3,3,1,2), ncol = 3, byrow=T) where in each row each number occurs only once. I'd like to define a permutation, e.g. 1 -> 2, 2 -> 1, 3 -> 3 and apply it to the matrix. Thus, the following matrix should result: m.perm <- matrix(c(2,1,3,1,2,3,3,2,1), ncol = 3, byrow=T) i.e. each 1 should map to 2 and vice

Dear all, Sometimes I have the situation where a function takes a data.frame and an additional argument describing come columns. For greater flexibility I want to allow for either column names or column indices. What I usually do then is something like the following: -------------8<------------- f <- function(datf, cols) { nc <- seq_along(datf) cn <- colnames(datf) colOK <-

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Dear all, Quite often I have the situation that I've multiple response variables and I create Linear Models for them in a function. The following code illustrates my usual approach: ---------------8<--------------- set.seed(123) dat <- data.frame(x = rep(rep(1:3, each = 3), 4), y = rep(1:3, 12)) dat$z1 <- rnorm(36, dat$x + dat$y) dat$z2 <- rnorm(36, dat$x + 2*dat$y) dat$z3 <-