similar to: Finding Missing Data Patterns

Hi All, I am compiling R-devel on Linux (Ubuntu 16.04.2) and that works just fine, but I am missing some of the expected features, as shown here: https://cran.r-project.org/doc/manuals/r-devel/R-admin.html#Linux In particular, after configure (using all defaults), I see: R is now configured for x86_64-pc-linux-gnu [...] Interfaces supported: X11 External libraries:

Hi All, After some tinkering, and with support from Duncan, I put together a package that allows for easy inclusion of MathJax equations in Rd files. The package has been submitted to CRAN, but those who want to try this out already can get it here: https://github.com/wviechtb/mathjaxr or in other words: install.packages("remotes")

Thanks Gabor and Duncan! It works. For those interested, I added this to the beginning of the \details{} section: \if{html}{\out{ <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax at 3/es5/tex-mml-chtml.js"> </script> }} And then I can use: \if{html}{\out{\(B_{x(a,b)} = \int_0^x t^{a-1} (1-t)^{b-1} dt\)}} or

Dear All, There might be a bug in heatmap(): x <- matrix(rnorm(10*5), 10, 5) heatmap(x, labCol=1:5) Error in axis(1, 1L:nc, labels = labCol, las = 2, line = -0.5, tick = 0, : 'at' and 'labels' lengths differ, 5 != 10 Works fine under 4.0.1. Looking at the code from 4.0.1 vs. Rdevel, esp. this part sticks out: labRow <- labRow[rowInd] %||% rownames(x) %||%

Hello Everybody, Is there a function available for calculating the density of a non-central t distribution? (dt does not accept the ncp option). Thanks in advance! -- Wolfgang Viechtbauer "Are you not thinking what I am not thinking?" -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Maybe a useful addition to the predict functions would be to return the values of the predictor variables. It just (unless there are problems) requires an extra line. I have inserted an example below. "predict.glm" <- function (object, newdata = NULL, type = c("link", "response", "terms"), se.fit = FALSE,

Dear All, I have a problem that I think could be solved much more efficiently, but I don't have a clue how to accomplish this. I have a matrix W with dimensions k*(p+1): Let's say W is 5*4 and looks like this: > W [,1] [,2] [,3] [,4] [1,] 1 -1 -1 1 [2,] 1 1 1 1 [3,] 1 2 -2 -1 [4,] 1 0 -1 -1 [5,] 1 -2 -1 0 I want to take

I have fitted a logistic regression model > failed.lr2$call lrm(formula = failed ~ Age + task2 + Age:task2, data = time.long, na.action = na.omit) using the Design package functions and would like to generate a nomogram from this model. the datadist information is generated and stored in > ddist time.long$Age time.long$task2 Low:effect 45

Hello List-Members, Let's say that I have the following code: for (i in c(10, 20, 30)) { for (j in c(200, 400, 600)) { ... ... x <- "something" * (code here) } } * Now, x is some result that I want to put into a results "matrix" that looks like this: 200 400 600 10 20 30 I came up with an ad-hoc solution adding some counters (called

Hi all, I am running Ubuntu 20.04.6 (focal) (yes, planning to upgrade soon) and just updated to 4.4.1. However, the process did not quite go as smoothly. 'sudo apt upgrade' ran but 'r-base-dev' was not updated because of a dependency issue: [08:57] ? wviechtb at wv-x5 ? ~/ ? sudo apt upgrade r-base-dev Reading package lists... Done Building dependency tree Reading state

I would like to define the order of the levels of a factor. The relevel function would work but since I have 20 levels I would prefer to declare the order explicitly. Using a smaller example levels(oldfactor) "b1" "b2" "r1" "r2" nufactor <- order(oldfactor,order=c("b1","r1","b2","r2")) # my fabricated function

Bonjour, Je voudrais savoir comment on peut modifier les capacit?s de m?moire pour le logiciel R, car j'ai un probl?me pour lire un tableau contenant 200000 observations et 30 variables. Je vous remercie d'avance pour toute aide ?ventuelle. Cordialement, Steffy.Ruiz at wanadoo.fr -------------- next part -------------- An HTML attachment was scrubbed... URL:

I would like to create a page of two graphs (2 rows by 1 col) and then draw vertical lines (segments?) on both graphs from the minimum values to the corresponding maximum value. So I have tried # > y <- rnorm(3000) > par(mfrow=c(2,1)) > plot(y,type="l") > plot(cumsum(y),type="l") > segments(1000,min(cumsum(y)),1000,max(cumsum(y))) > par(mfg=c(1,1)) >

Interesting. I gave this a try, but couldn't make this work. One would have to infuse something like <script id="MathJax-script" async src="https://cdn.jsdelivr.net/npm/mathjax at 3/es5/tex-mml-chtml.js"> </script> or <script id="MathJax-script" async src="<url-to-your-site>/mathjax/tex-chtml.js"> </script> into

I am trying to pass an equation as an arguement to a function, which seems pretty straightforward given lazy evaluation. I constructed the following little test to make sure I sort of knew what I was doing: go <- function(X,eq) { C <<- X*2; d <<- eq} a _ rnorm(100) go(10,eq=a[.5*length(a)]+C+1) > C [1] 20 > d [1] 21.10551 > a[.5*length(a)] [1] 0.1055086 Everything

I was not sure who I should contact about this, so I am posting this here. There are a few broken links on the R website. 1) http://www.r-project.org/search.html -> link to the Nabble R Forum. I belive the correct/new URL should be: http://r.789695.n4.nabble.com/ 2) http://www.r-project.org/other-docs.html -> link to "Auswertung ?kologischer Daten". Not sure if there is a new

Hello All, I am wondering if there has ever been any discussion/consideration given to incorporating MathJax (or something similar) into R for rendering equations in .Rd files. I know that equations are rendered beautifully in the pdf manuals, but I suspect the majority of users primarily look at the html help files when using R. While I am comfortable reading something like "B_x(a,b) =

Hi, I have been looking for an R package which allowed to do meta-analysis (both pairwise and network/mixed-treatment) at arm-level rather than at trial-level, the latter being the common way in which meta-analysis is done. By arm-level meta-analysis I mean one that accounts for data provided at the level of the individual arms of each trial and that does not simply derive the difference between

Dear All, The metafor package currently fails CRAN checks on Sparc Solaris: http://cran.r-project.org/web/checks/check_results_metafor.html The problem is probably due to an unintended (= stupid) use of identical() in a couple tests. I have changed that to more appropriate tests using all.equal(). However, before I resubmit the package to CRAN, I would really like to make sure that the updated

> -----Original Message----- > From: Kurt Hornik <Kurt.Hornik at wu.ac.at> > Sent: Friday, October 11, 2024 14:18 > To: Viechtbauer, Wolfgang (NP) <wolfgang.viechtbauer at maastrichtuniversity.nl> > Cc: r-devel <r-devel at r-project.org> > Subject: Re: [Rd] Error message when calling t.test() and aov() with a factor > variables > > >>>>>