search for: bedevilled

Dear R-help, First of all, thank you VERY much for any help you have time to offer. I greatly appreciate it. I would like to write a function that, given an arbitrary number of factors from a data frame, tabulates the number of occurrences of each unique combination of the factors. Cleary, this works: > table(horse,date,surface) <SNIP> , , surface = TURF

hi chaps: a simple suggestion: R tells me who the contributors() are, but this should also tell me where I should mail suggestions to. Is it this mailing list? a repository of suggestions? an individual? this came up because i wanted to suggest two small enhancements: the first is for the summary() method for plain data frames. it would seem to me that the number of "NA"s

I've noticed quite a few messages relating to large data sets bedeviling R users, and having just had to program my way through one that actually caused a "Bus error" when I tried to read it in, I'd like to ask two questions. 1) Are there any facilities for aggregation of data in R? ( I admit that this will not do much for the large data set problem immediately) 2) Is there any

For the question at the end, try barplot with the horiz=TRUE argument. Date: Tue, 24 Feb 2004 09:30:21 -0500 From: ivo welch <ivo.welch at yale.edu> To: <r-help at stat.math.ethz.ch> Cc: <r-help-owner at stat.math.ethz.ch>,ivo welch <ivo.welch at yale.edu> Subject: [R] Suggestions ?!?! hi chaps: * I have some suggestion, the first of which is about

What''s the best way to specify the width of a TextCtrl in characters instead of pixels? -- R. Mark Volkmann Partner, Object Computing, Inc.

How does one rotate the loadings from a principal component analysis? Help on function prcomp() from package mva mentions rotation: Arguments retx a logical value indicating whether the rotated variables should be returned. Values rotation the matrix of variable loadings (i.e., a matrix whose olumns contain the eigenvectors). The function princomp returns this in the element

While working on 'random walk' applications, I got interested in optimizing noisy objective functions. As an (artificial) example, the following is the Rosenbrock function, where Gaussian noise of standard deviation `sd = 0.01` is added to the function value. fn <- function(x) (1+rnorm(1, sd=0.01)) * adagio::fnRosenbrock(x) To smooth out the noise, define another

(1) ?cbind claims The generic functions `cbind' and `rbind' take a sequence of vector and/or matrix arguments and combine them as the columns or rows, respectively, of a matrix. Note: The method dispatching is not done via `UseMethod(..)', but by C-internal dispatching. Therefore, there's no need for, e.g., `rbind.default'. but my cbind.ts