similar to: pairs plot

Possibly because: panel.hist is not an existing R function -- you have to first create it so pairs() can use it. ?pairs shows you how in the Help examples, i.e. panel.hist <- function(x, ...) { usr <- par("usr") par(usr = c(usr[1:2], 0, 1.5) ) h <- hist(x, plot = FALSE) breaks <- h$breaks; nB <- length(breaks) y <- h$counts; y <- y/max(y)

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

On Tue May20'25 05:56:59AM, Rui Barradas wrote: > From: Rui Barradas <ruipbarradas at sapo.pt> > Date: Tue, 20 May 2025 05:56:59 +0100 > To: Ranjan Maitra <mlmaitra at gmx.com>, r-help at r-project.org > Subject: Re: [R] how to read a PSB file in R? > > ?s 03:17 de 20/05/2025, Ranjan Maitra via R-help escreveu: > > I have come across this file (warning,

Hi, I have modified the USJudgeRatings data (available in R) to illustrate my question. # Use the first 4 variables of USJudgeRatings and add a group variable with two levels USJudgeRatings <- USJudgeRatings[,1:4] USJudgeRatings$group <- factor(c(rep(1, 22), rep(0, 21))) # I can draw a pairs graph where members of each group are drawn in different colors: pairs(USJudgeRatings[,1:4], col

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

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

Hi, First of all, thanks for the efforts of all the developers and contributors - I'm very new to R and at the moment am just using it to create some graphics, but it seems to be quite powerful. I've googled the archives and wasn't able to find anyhting that dealt with this problem, so would appreciate any suggestions/tips. In a pairs plot I'd like to plot a linear regression line

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

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

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) from the gtools package. However, what if clockwise or counterclockwise arrangements are the same? I know that half of the above (n - 1)! arrangements are redundant. Is there an easy way to

?s 03:17 de 20/05/2025, Ranjan Maitra via R-help escreveu: > I have come across this file (warning, massive, 4.3 GB) https://esahubble.org/media/archives/images/original/heic1502a.psb and it appears to be a filetype I was not aware of previously. > > Is it possible to read the file in R using any tool? It is an image and I am looking for the RGB of the file. > > Many thanks and

> 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

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)

Dear all, I have been looking for a while for ways to simulate from Langevin distributions and I thought I would ask here. I am ok with finding an algorithmic reference, though of course, a R package would be stupendous! Btw, just to clarify, the Langevin distribution with (mu, K), where mu is a vector and K>0 the concentration parameter is defined to be: f(x) = exp(K*mu'x) / const where

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 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 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",

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