similar to: Maximum likelihood estimate ofbivariatevonmises-weibulldistribut

r-help at stat.math.ethz.ch on Wednesday, October 26, 2005 at 6:00 AM -0500 wrote: Ronaldo, Try Harold's suggestion. The df still won't agree, because lmer (at least in its current version) just puts an upper bound on the df. But that should be OK, because all those t tests are approximations anyways, and you can get better confidence intervals (credible intervals, whatever) by using the

Long ago (Sat, 2 Nov 2002), Bill Hart <w.hart at sbcglobal.net> wrote: > An R newbie here. I am using R 1.6 currently and have > (successfully, I think) installed the Foreign package. > Tried to import a data file created with Stata 7.0 > SE. Had minor problems with syntax then R decided > that my file was not really a Stata file. It rejected > the file saying

In the R code of Mardia's test, what does the line " x1 = x[x[, p] == i, -p]" mean? Thanks a lot! function (x) { p = dim(x)[2] f = p - 1 clases = length(table(x[, p])) for (i in 1:clases) { x1 = x[x[, p] == i, -p] ndat = dim(x1)[1] mo3 = mo3(x1) mard1 = ndat * mo3/6 cat("Mardia's test for class", i,

helpeRs, I have a nice looking mosaic plot in an article to be published soon. Sadly, the published version will be in black and white and so ruin the advantage of the default shading scheme of tiles. What would readers suggest as an alternative shading scheme? If I have a black-and-white shading scheme graduated according to suitable cutoffs I won't be able to tell positive from

> On Jan 18, 2018, at 7:49 AM, Anjali Karol Nair <anjali232 at gmail.com> wrote: > > Hi, > > I want to convert my MATLAB programs to R studio programs. > Kindly guide on the same. Hi, Using Google with a search phrase such as "MATLAB to R" will yield a number of possible resources for you such as: http://www.math.umaine.edu/~hiebeler/comp/matlabR.pdf which

hello, I'm Tom?s, an student from Spain. Firstly, congratulations for your codecs. Imagine that you are very busy. So I'm very grateful if you read my mail. Hi, i have a big problem with my Diploma Work. I have a new audio codec and i want integrate it in Windows Media 9 or higher. So i download your codec (source code). I have been investigating many archives of your code. My

Dear R users, I have been having problems getting believable estimates from anova on a model fit from lmer. I get the impression that F is being greatly underestimated, as can be seen by running the example I have given below. First an explanation of what I'm trying to do. I am trying to fit a glmm with binomial errors to some data. The experiment involves 10 shadehouses, divided between

Dear all, I got this error message > library(dprep) > mardia(Savg) Error in cov(data) : 'x' is empty But with the same data, I got > library(mvnormtest) > mshapiro.test(Savg) Shapiro-Wilk normality test data: Z W = 0.9411, p-value = 0.6739 What does the error message "Error in cov(data) : 'x' is empty" mean? Thanks a lot! Jiao

Thanks Dimitris!!! That's much clearer now. Still have a lot of work to do this weekend to understand every bit but your code will prove very useful. Cheers, Aziz -----Original Message----- From: Dimitrios Rizopoulos [mailto:Dimitris.Rizopoulos at med.kuleuven.be] Sent: May 12, 2006 4:35 PM To: Chaouch, Aziz Subject: RE: [R] Maximum likelihood estimate of bivariate

A bit of a newbee to R and factor rotation I am trying to understand factor rotations and their implementation in R, particularly the GPArotation library. I have tried to reproduce some of the examples that I have found, e.g., I have taken the values from Jacksons example in "Oblimin Rotation", Encyclopedia of Biostatistics

Hi, I want to convert my MATLAB programs to R studio programs. Kindly guide on the same. [[alternative HTML version deleted]]

Hello! Is it posible to apply /cumsum()/ along the 3rd dimension of 3D array? Something like matrlab function - /cumsum (*A*,dim)/ which returns the cumulative sum of the elements along the dimension of *A* specified by scalar dim. Thanks in advance ?eljka -- View this message in context: http://r.789695.n4.nabble.com/cumsum-in-3d-arrays-tp4110470p4110470.html Sent from the R help mailing

Good Night I made different test to check normality and multinormality in my dataset, but I don´t know which test is better. To verify univariate normality I checked: shapiro.test, cvm.test, ad.test, lillie.test, sf.test or jaque.bera.test and To verify multivariate normal distribution I use mardia, mvShapiro.Test, mvsf, mshapiro.test, mvnorm.e. I have a dataset with almost 1000 data and 9

Hi everyone, Can I suggest an additional output component in cancor, from package mva? It would be useful to have the number of canonical correlation vectors, equivalently the rank of the covariance between x and y (label "rank"). This would usually be min(dx, dy), where dx and dy have already been computed for the svd function, but there might be situations where it was less than

Dear R developers, there appears to be a small problem with function cmdscale: for non-Euclidean distance matrices, using option add=FALSE (the default), cmdscale misses the smallest eigenvalue. This affects GOF statistic g.1 (See Mardia, Kent + Bibby (1979): Multivariate Analysis, eq. (14.4.7). The corresponding formula in Cox + Cox (2001): Multidimensional Scaling, 2nd ed., p 38, would

Hi, there. I have two questions about the diagnostics in multivarite statistics. 1. Is there any diagnostics tool to check if a multivariate sample is from multivariate normal distribution? If there is one, is there any function doing it in R? 2. Is there any function of testing if two multivariate distribution are same, i.e. the multivariate extension of Kolomogrov-Smirnov test? Thanks for

Hi All, This is a question not directly related to R itself, it's about how to deal with missing data. I want to build wind roses i.e. circular histograms of wind directions and associated speeds to look for trends or changes in the wind patterns over several decades for some meteo stations. The database I have contains hourly records of wind direction and speed over the past 50

My previous post about prcomp and princomp was done in some haste as I had long ago indicated to Kurt that I would try to have this ready for the June release, and it appeared that I would miss yet another release. I also need to get it out before it becomes hopelessly buried by other work. Brian Ripley kindly pointed out some errors, and also pointed out that I was suggesting replacing some

I was wandering if anybody ever tried to compare the classification accuracy of nnet to other (rpart, tree, bagging) models. From what I know, there is no reason to expect a significant difference in classification accuracy between these models, yet in my particular case I get about 10% error rate for tree, rpart and bagging model and 80% error rate for nnet, applied to the same data. Thanks.

On Wed, Jan 15, 2020 at 2:31 PM David Greene via llvm-dev < llvm-dev at lists.llvm.org> wrote: > Emilio Cobos Álvarez <emilio at crisal.io> writes: > > > [1] or [2] are recentish examples that come to mind, but it happens > > fairly often. Of course for a bunch of simpler changes one revision is > > enough. > > I think you forgot to include links. :)