similar to: Re: errors in randomization test

Dear All I am trying to do a repeated measures analysis using lmer and have a number of issues. I have non-orthogonal, unbalanced data. Count data was obtained over 10 months for three treatments, which were arranged into 6 blocks. Treatment is not nested in Block but crossed, as I originally designed an orthogonal, balanced experiment but subsequently lost a treatment from 2 blocks. My

Hi all, I am very new to R and this might be a simple question but I have looked everywhere you suggest before writing to you. I am trying to change font type from san-serif to a serif (Times New Romans) on all labels and axis of my boxplot. I have used this function in other plots before, e.g.: plot(residuals~lnlifespan, data=mydata, pch=psymb, font=6, xlab="ln reproductive

In checking over the solutions to some homework that I had assigned I observed the fact that in R (version 2.4.0) pnorm(-1.46) gives 0.07214504. The tables in the text book that I am using for the course give the probability as 0.0722. Fascinated, I scanned through 5 or 6 other text books (amongst the dozens of freebies from publishers that lurk on my shelf) and found that some agree with R

Hi, I'm running a GLMM on binomial choice data. The outputs I receive are sensible except for the degrees of freedom, which come out much larger than expected. Can anyone advise please? Exptl design: Response = Choice Fixed Factors = Position, Treatment and Sex Random Factor = ID nested within Treatment and Sex Covariate = Delay The model: glmmPQL(FreeChoice ~ Position * Treatment + Sex

Hello, For verbose coding I'd like to do something like: > myfunction <- function(x){ > if (a){ > stop(paste(myfunction_name_here,"requires xyz!") > } Is that possible? Thanks for any hints, Joh

Just now I again had occasion to want nested describe lists in a documentation file. I found that the bug which I reported on 18 October, 2001 still persists. I checked on the bug report at the R web page, and found that the notes say ``Not a problem in R 1.4.0 (2001-12-08)''. Well, it's still a problem for me --- using R 1.4.1. (Details: platform sparc-sun-solaris2.7 arch

Hi wizards, I need to know how can I generate this numbers I have n numbers N1,N2 , Nn , but Nn = 1- sum(N1+N2+...+Nn-1) and sum(N1+N2+..Nn)=1 and N1,N2,..Nn with 0<N<1 . Does somebody know how to generate it ? Some distribution or algorithm. Thanks in advance. -- Web Page http://www.geocities.com/ricardo_rios_sv/index.html

Apologies for the off-topic question; as usual I'm trying to draw upon the unparalleled knowledge and sagacity of the r-help list. Please reply off-list if you can help me out. A collaborator of mine found a formula we need, on sheets which he had photocopied out of a book, some years ago. He cannot remember which book (he's getting to be as senile and forgetful as I am, poor bloke!).

I have just been bitten by a quirk in the behaviour of model.matrix. I used model.matrix inside a function, and passed to it a formula that was built elsewhere. The formula was of the form ``y ~ x + w + z''. Now, model.matrix cheerfully accepts formulae of this form, although it only ***needs*** the right hand side, i.e. ``~ x + w + z'' --- the ``y'' can be dropped (but

Hi, I am facing the problem that I want to plot a histogram chart set freq to true and overlay with normal or weibull or exponential distribution curve. The sample code is shown as below: >samp<-c(-8.2262,-8.2262,-8.2262,-8.20209,-8.09294,-8.07321,-8.07321, -8.07321,-8.07175,-8.04948,-8.04948,-8.04948,-8.03848,-8.03848,

Dimitris Rizopoulos wrote: > look at ?rowMeans; you can also use "apply(mat, 1, mean)" but > rowMeans() is better. By my reading of the question, this is not what Ezhil wants. He said: ``I have a 992 x 74 matrix. I would like to form a new matrix by averaging each 4 rows from the original one.'' I.e. he wants (I think) the first row of the new matrix to be the

Colin, If your propose is to create a ternary plot with points and vectors, I think easier do this with graphics based plots instead of trellis based plots. Although, with little work you can do with trellis too. I gave you a reproducible code to put an arrow in a ternary plot. I use the function locator() to extract coordinates. The code is the following

I mis-spoke. It seems I had two collections of functions in the same directory. One by Colin Goodall, and one by David Scott (I have no record of where he is/was located). It is the *latter* collection that does all its work from within Fortran. I'll have another look at what Colin Goodall actually wrote to see if it could be useful to guarav. cheers, Rolf Turner rolf at

I've built R functions to ``effect'' a particular distribution, and would like to find out if that distribution is already ``known'' by an existing name. (I.e. suppose it were called the ``Melvin'' distribution --- I've built dmelvin, pmelvin, qmelvin, and rmelvin as it were, but I need a real name to substitute for melvin.) The distribution is really just a toy

After some futile searches, I decided to ask the list to see if any of the sages out there would have an answer: I have a function I wrote a few years ago in S, which calls glim numerous times. I'd like to port it to R, but glm works differently from glim, which takes as part of its input an X design matrix. I probably could write a function to convert glim to glm, but hope this

Hi All R experts I have data in a two dimensional table. each row of the data adds upto 100 ( hence they are percentages ). it can be interpreted as like this A - I are the matches and P - X are the players. Thus Player P scored 20% of the runs during this season in Match C, 60% in Match D and remaining 20% in Match G. I want to plot 3-d bar plot, where X axis have players, Y axis have

I've looked through the FAQ and can't find anything about this. I'm working on a Sun machine, running Solaris 2.7. I'm a new R-user; have been using Splus for millenia, and finally decided it was time I got going with R. So I downloaded R, installed it, fiddled about a bit, and found that command-line editing was absent. Scrounging through the documentation some more, I saw it

I don't know from the nortest package, but it should ***always*** be the case that you test hypotheses H_0: The data have a normal distribution. vs. H_a: The data do not have a normal distribution. So if you get a p-value < 0.05 you can say that ***there is evidence*** (at the 0.05 significance level) that the data are not from a normal distribution. If the nortest package does

What R functionnalities are there to do missing values imputation (substantial proportion of missing data)? I would prefer to use maximum likelihood methods ; is the EM algorithm implemented? in which package? Thanks Anne ---------------------------------------------------- Anne Piotet Tel: +41 79 359 83 32 (mobile) Email: anne.piotet@m-td.com

If one specifies new options in a package, using the options() function, where does/should one document these new options? E.g. suppose that I put the line options(melvin=42) in a file zzz.R in the R directory of the package source, where the package contains functions foo(), bar(), clyde(), and irving() which all query options("melvin") and take some action based on the value of