similar to: getting all circular arrangements without accounting for order

Thanks! Yes, however, this seems a bit wasteful. Just wondering if there are other, more efficient options possible. Best wishes, Ranjan On Thu, 29 Mar 2018 22:20:19 -0400 Boris Steipe <boris.steipe at utoronto.ca> wrote: > If one is equal to the reverse of another, keep only one of the pair. > > B. > > > > > On Mar 29, 2018, at 9:48 PM, Ranjan Maitra

If one is equal to the reverse of another, keep only one of the pair. B. > On Mar 29, 2018, at 9:48 PM, Ranjan Maitra <maitra at email.com> wrote: > > Dear friends, > > I would like to get all possible arrangements of n objects listed 1:n on a circle. > > Now this is easy to do in R. Keep the last spot fixed at n and fill in the rest using permuations(n-1, n-1)

I don't know if this is more efficient than enumerating with distinct directions and weeding... it seems kind of heavyweight to me: ####### library(gtools) directionless_circular_permutations <- function( n ) { v <- seq.int( n-1 ) ix <- combinations( n-1, 2 ) jx <- permutations( n-3, n-3 ) x <- lapply( seq.int( nrow( ix ) ) , function( i ) {

Jeff, I wanted to let you know that your function is faster than generating the directional circular permutations and weeding. Here is the time for n = 10. I compared with just doing the permutations, there is no point in proceeding further with the weeding since it is slower at the start itself. system.time(directionless_circular_permutations(10)) user system elapsed 1.576 0.000

New function below is a bit faster due to more efficent memory handling. for-loop FTW! directionless_circular_permutations2 <- function( n ) { n1 <- n - 1L v <- seq.int( n1 ) ix <- combinations( n1, 2L ) jx <- permutations( n-3L, n-3L ) jxrows <- nrow( jx ) jxoffsets <- seq.int( jxrows ) result <- matrix( n, nrow = factorial( n1 )/2L, ncol = n ) k

Dear all, I have a question with regard to the use of hclust. I would like to be able to specify my own distance matrix instead of asking R to compute the distance matrix for me. It is computationally easier for me this way. My question is: How can I get hclust to accept this? Thanks, Ranjan -- *************************************************************************** Ranjan

Dear friends, Is there a way to read data files written in lisp into R? Here is the file: https://archive.ics.uci.edu/ml/machine-learning-databases/university/university.data I would like to read it into R. Any suggestions? Thanks very much in advance for pointers on this and best wishes, Ranjan -- Important Notice: This mailbox is ignored: e-mails are set to be deleted on receipt. Please

Dear friends, Sorry for this somewhat generically titled posting but I had a question with using contrasts in a manova context. So here is my question: Suppose I am interested in doing inference on \beta in the case of the model given by: Y = X %*% \beta + e where Y is a n x p matrix of observations, X is a n x m design matrix, \beta is m x p matrix of parameters, and e is a

Dear list, I have been using the Rmath library for quite a while: in the current instance, I am calling dnt (non-central t density function) repeatedly for several million. When the argument is small, I get the warning message: full precision was not achieved in 'pnt' which is nothing unexpected. (The density calls pnt, if you look at the function dnt.) However, to have this happen a

Dear colleagues, I have an image which I can display in the greyscale using image. On this image, for some pixels, which I know, I want to display their activity based on a third measure. One way to do that would be to color these differently, and use an opacity measure to display the third measure. An example of what I am trying to do is at:

Dear colleagues, I had a question wrt the car package. How do I evaluate whether a simpler multivariate regression model is adequate? For instance, I do the following: ami <- read.table(file = "http://www.public.iastate.edu/~maitra/stat501/datasets/amitriptyline.dat", col.names=c("TCAD", "drug", "gender", "antidepressant","PR",

Thanks! I am trying to use it in R. (Actually, I try to give my students experiences with different kinds of files and I was wondering if there were tools available for such kinds of files. I don't know Lisp so I do not actually know what the lines towards the bottom of the file mean.( Many thanks for your response! Best wishes, Ranjan On Wed, 17 Jan 2018 20:59:48 -0800 David Winsemius

Hello, I have been wondering of an efficient way to do this: I have an n x m x p array Z and a p x n matrix Y. I want to multiply each of the n matrices with the corresponding column vector of Y. In other words, I am wanting to matrix multiply: Z[i, ,] %*% Y[, i] which will give me a (two-dimensional) array or matrix of dimension n x p with the i'th row storing the above. Any pointers

> On Jan 17, 2018, at 8:22 PM, Ranjan Maitra <maitra at email.com> wrote: > > Dear friends, > > Is there a way to read data files written in lisp into R? > > Here is the file: https://archive.ics.uci.edu/ml/machine-learning-databases/university/university.data > > I would like to read it into R. Any suggestions? It's just a text file. What difficulties

Can someone please point me to an example with geom_contour() that uses a function? The help does not have an example of a function, and also I did not find anything from online searches. TIA, BFD ----------------------------------------------------------------------------------------------- How about geom_contour()? Am So., 8. Okt. 2017, 20:52 schrieb Ranjan Maitra <maitra at

It seems the file contains records, with each record having 18 fields. I would use awk (standard unix tool), creating an awk script to process the file into a new file with one line for each record, each line with 18 fields, say comma-separated. The csv file can then be easily read into R via the function read.csv. HTH, Eric On Thu, Jan 18, 2018 at 6:22 AM, Ranjan Maitra <maitra at

Dear friends, I have two questions regarding the use of lattice. First some code: ## begin code z <- cbind(rep(c("BIC", "ICL", "s_v", "Q_v", "sig-q", "s_lsk", "s_lML", "s_mlsk", "s_mlML", "s_la8", "s_haar"), each = 250), rep(c(5, 10, 20, 30, 50), each = 50)) z

Dear friends, Is there an easy way of commenting out a block of R code after it has been written? (I am aware that R-aware editors can insert # line-by-line while it is being written, but I want to basically block out chunks of R code in a few strokes.) This question was asked on this mailing list some time ago: Professor Ripley's answer was to try the following:

Hi, I want to test for a contrast from a regression where I am regressing the columns of a matrix. In short, the following. X <- matrix(rnorm(50),10,5) Y <- matrix(rnorm(50),10,5) lm(Y~X) Call: lm(formula = Y ~ X) Coefficients: [,1] [,2] [,3] [,4] [,5] (Intercept) 0.3350 -0.1989 -0.1932 0.7528 0.0727 X1 0.2007 -0.8505 0.0520

Hi, How does one change the dot for the median in a boxplot drawn using lattice? I have been looking at > names(trellis.par.get()) [1] "grid.pars" "fontsize" "background" [4] "panel.background" "clip" "add.line" [7] "add.text" "plot.polygon"