similar to: using lme on multiple datasets in one shot

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

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",

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 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 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:

Dear colleagues, I am trying to get someone to use R on MS Windows with the browser disabled. My question is how does he/she get to use R-help which goes off the browser (and correspondingly complains about the inability to start firefox, etc). In linux, which is what I use, this is not a problem: what needs to be set in Windows to replicate this behavior? Sorry if I am not clear: please feel

Hi, I am trying to convert some Matlab code into R for running some experiments and I was wondering if there is some function in R which does the work of the gradient function in Matlab calculating the "gradient" of 1-, 2- and 3-d images. I only need the 3-d calculations for running these experiments. Many thanks and best wishes, Ranjan

I guess the question that is being asked here is what is the scaling matrix that is being returned in the qda object. The help file on qda() says: ... scaling: for each group ?i?, ?scaling[,,i]? is an array which transforms observations so that within-groups covariance matrix is spherical. ... This is a bit ambiguous. I tried a few cases (spectral, QR decomposition, especially given that it is an

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

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

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

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

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

> 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 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

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

The file also has a bunch of email headers stuck in the middle of it: ..... (QUALITY-OF-LIFE SCALE:1-5 4) (ACADEMIC-EMPHASIS HEALTH-SCIENCE) ) ------- ------- >From LEBOWITZ at cs.columbia.edu Mon Feb 22 20:53:02 1988 Received: from zodiac by meridian (5.52/4.7) Received: from Jessica.Stanford.EDU by ads.com (5.58/1.9) id AA04539; Mon, 22 Feb 88 20:59:59 PST Received: from