similar to: how to overlay 2d pdf atop scatter plot using ggplot2

Hi, I am no expert on ggplot2 and I do not know the answer to your question. I looked around a bit but could not find an answer right away. But one possibility could be, if a direct approach is not possible, to draw ellipses corresponding to the confidence regions of the multivariate t density and use geom_polygon to draw this successively? I will wait for a couple of days to see if there is a

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

Hello Ulrik, I apologize, but I can not see how to provide a pdf in place of the density function which calculates a KDE (that is, something from the dataset in the example). Can you please point to the specific example that might help? Here is what I get: require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(faithfuld, aes(waiting,

Hi, This is not a HW problem, sadly: I was last in a classroom 30 years ago, and can no longer run off to the instructor :-( I apologize but I cut and paste the wrong snippet earlier and made a typo in doing so, but the result is the same with the more appropriate snippet. require(mvtnorm) require(ggplot2) set.seed(1234) xx <- data.frame(rmvt(100, df = c(13, 13))) v <- ggplot(data = xx,

library(mvtnorm) # you were misusing "require"... only use require if you plan to library(ggplot2) # test the return value and fail gracefully when the package is missing set.seed( 1234 ) xx <- data.frame( rmvt( 100, df = c( 13, 13 ) ) ) xx2 <- expand.grid( X1 = seq( -5, 5, 0.1 ) # all combinations... could be used to fill a matrix , X2 = seq( -5, 5, 0.1 )

Hi BFD, ?geom_contour() *does* have helpful examples. Your Google-foo is weak: Searching for geom_contour brought me: http://ggplot2.tidyverse.org/reference/geom_contour.html as the first result. HTH Ulrik On Mon, 9 Oct 2017 at 08:04 Big Floppy Dog <bigfloppydog at gmail.com> wrote: > Can someone please point me to an example with geom_contour() that uses a > function? The help

> On Oct 9, 2017, at 6:03 AM, Big Floppy Dog <bigfloppydog at gmail.com> wrote: > > Hello Ulrik, > > I apologize, but I can not see how to provide a pdf in place of the density > function which calculates a KDE (that is, something from the dataset in the > example). Can you please point to the specific example that might help? > > Here is what I get: > >

Hi, I am looking for an efficient way to compute the values of the density function of a multivariate T distribution - something like "dmvnorm", but for T distr. Does this exist somewhere? Many thanks, Jan Bulla Goettingen University

Is there any way to know how the "dmvt" function computes the hypergeometric function needed in the calculation for the density of multivariate t distribution? -- View this message in context: http://r.789695.n4.nabble.com/hypergeometric-function-in-mvtnorm-tp4483730p4483730.html Sent from the R help mailing list archive at Nabble.com.

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,

Hello, R-List, I'm getting error messages when adding geom_density2d() [package ggplot2]: ============================================================================ Fehler in pretty(range(data$z), 10) :   NA/NaN/Inf in externem Funktionsaufruf (arg 1) Zusätzlich: Warnmeldungen: 1: Removed 10000 rows containing missing values (stat_contour). 2: In min(x) : kein nicht-fehlendes Argument für

Hello, I want to draw a histogram of the mean of sample observations drawn from multivariate t distribution. I am getting the following error corresponding to the code I used. Though I am getting the graph, but I am curious to know the warning message. Warning messages: 1: In if (freq) x$counts else { : the condition has length > 1 and only the first element will be used 2: In if (!freq)

Hi, Are there some packages which can generate multi-normal, multi-t, etc multivariate sampling? thanks! Best wishes, Peng ******************************* Peng Zhang Department of Biostatistics Harvard School of Public Health 655 Huntington Avenue Boston, Massachusetts 02115 ******************************* I believe I can fly I believe I can touch the sky

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

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

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 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

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

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 ) {

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