similar to: How to test the difference between paired correlations?

Thank you, but this now sounds more difficult: what would be the point in having these ready-made functions if I have to do it manually? Anyway, How would I implement the last part? On Thu, Mar 23, 2023 at 1:23?AM Ebert,Timothy Aaron <tebert at ufl.edu> wrote: > > If you are open to other options: > The null hypothesis is that there is no difference. > If I have two equations

My guess: It I clear from the link that they can use the R logo for commercial purposes. The issue is what to do about the "appropriate credit" and "link to the license." How would I do that on a hoodie? Would they need a web address or something? -----Original Message----- From: R-help <r-help-bounces at r-project.org> On Behalf Of John Fox Sent: Tuesday, March 21, 2023

I may be missing something but using the plain old c() combine function seems to work fine: df <- data.frame(left = 1:5, right = 6:10) df.combined <- data.frame(comb = c(df$left, df$right)) df left right 1 1 6 2 2 7 3 3 8 4 4 9 5 5 10 df.combined comb 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 -----Original

Sorry about that, let me check the correct version for the intrin0.h include guard. //Marcus ________________________________ From: Ralph Giles <giles at thaumas.net> Sent: Thursday, June 11, 2020 19:31 To: Marcus Asteborg <xnorpx at outlook.com>; opus at xiph.org <opus at xiph.org> Subject: Re: [opus] Misc patches Speaking of needing more complete ci feedback, the intrin0.h

Hi, You were on the right track using stack(), but you just pass the entire data frame as a single object, not the separate columns: > stack(NamesWide) ? values ? ind 1 ? ?Tom Name1 2 ? Dick Name1 3 ?Larry Name2 4 ?Curly Name2 Note that stack also returns the index (second column of 'ind' values), which tells you which column in the source data frame the stacked values originated

Hello everbody, I want to generate different subsets of my data-set and safe this subsets with names listet in a vector. Because in reality I have got about 70 subsets I want to realize this in a loop Somehow like this: names=c("nam1",

Just to repeat: you have NamesWide<-data.frame(Name1=c("Tom","Dick"),Name2=c("Larry","Curly")) and you want NamesLong<-data.frame(Names=c("Tom","Dick","Larry","Curly")) There must be something I am missing, because NamesLong <- data.frame(Names = c(NamesWide$Name1, NamesWide$Name2)) appears to

It's still hard to figure out what you want. If you have two vectors you can compute their (2x2) covariance matrix using cov(cbind(x,y)). If you want to compute all pairwise squared differences between elements of x and y you could use outer(x, y, "-")^2. Can you explain a little bit more about (1) the context for your question and (2) why you want/need to use apply() ? On

Hi guys, I am using the cor() function to see if there are correlations between March cortisol levels and December cortisol levels and I'm trying to figure out if the function is doing what I want it to do. Each sample has it's own separate row in the CSV file that I'm working out of. March Cort and December Cort are different columns and they come from separate samples, therefore

We are currently analyzing data on children clustered in day care-centers (DCC). We have tried to use geepack and gee libraries to estimate an overall incidence rate for absences (=number of absences/risk time) by specifying geese(number.absences ~ offset(log(risktime)), id=day.care.id, family=poisson("log"), data=dcc, corstr="exch",

Fair enough. You do not put citations in the abstract or summary. The level of detail in the methods can be modified by including a link to a repository or by including supplemental material, or appendix, or foot notes, or something equivalent. If all programs/packages are used with system defaults the version number is sufficient. If the packages are customized and such customization materially

Hi, Here are 3 suggested patches. 1. Build test for cmake and run the test in gitlab-ci. 2. Disable the message box on Windows on abort that cause test hangs in CI. 3. Build time improvement by removing unnecessary includes of stdio.h in production code and change to a lighter header intrin.h -> intrin0.h (windows only). Attached screenshot of measurement but it resulted in 14%

I suggest to add a new function to create a vector of n ``contiguous'' colors with tails in two colors. This function is similar to `cm.colors' but the colors can be choosen by hsv values. This function could be used e.g. as alternative to the default ``col.regions'' in `levelplot'. Perhaps the arguments in the following code could be simplified. Wolfram Fischer #---

While using the Hodges Lehmann Mean in DescTools (DescTools::HodgesLehmann), I found that it generated incorrect answers (see <https://github.com/AndriSignorell/DescTools/issues/97> https://github.com/AndriSignorell/DescTools/issues/97). The error is driven by the existence of tied values forcing wilcox.test in Base R to switch to an approximate algorithm that returns incorrect results - see

The _point_ is to explain the story of the research so people can compare easily with other work. A story interrupted by tedious details is not very comprehensible. And I _did_ recommend providing a link to a code repository and using reproducible coding tools. On December 30, 2024 7:35:37 PM PST, "Ebert,Timothy Aaron" <tebert at ufl.edu> wrote: >Maybe I misunderstand, but if

Greetings, I am having a problem with DescTools::Quantile (a function computing quantiles from weighted samples): # these sum to one probWeights = c( 0.0043, 0.0062, 0.0087, 0.0119, 0.0157, 0.0204, 0.0257, 0.0315, 0.0378, 0.0441, 0.0501, 0.0556, 0.06, 0.0632, 0.0648, 0.0648, 0.0632, 0.06, 0.0556, 0.0501, 0.0441, 0.0378, 0.0315, 0.0257, 0.0204, 0.0157, 0.0119, 0.0087,

It looks like a homework assignment. It also looks like you didn't read the documentation carefully enough. The 'len.out' argument in seq is solely for specifying the length of a sequence. The 'quantile' function omputes the empirical quantile of raw data in the vector 'x' at cumulative probabilit(y)(ies) given in the weights' argument, with interpolation I'm

On 2024-09-07 7:37 p.m., Jeff Newmiller wrote: > I tried it on R 4.4.1 on Linux Mint 21.3 just before I posted it, and I just tried it on R 3.4.2 on Ubuntu 16.04 and R 4.3.2 on Windows 11 just now and it works on all of them. > > I don't have a big-endian machine to test on, but the Unicode spec says to honor the BOM and if there isn't one to assume that it is big-endian data.

Hi Everyone, Following the previous discussion on optimizing *wilcox functions, Andreas Loeffler brought to my attention a few other bugs in `wilcox` family functions. It seems like these issues have been discussed online in the past few months, but I haven?t seen discussion on R-devel...unless I missed an email, it seems like discussion never made it to the mailing list. I haven?t seen any bug

¿Alguien sabe si el test de reacciones extremas de Moses está escrito en algún paquete de R? Gracias de antemano.