search for: xappli

`outer` (and related functions like kronecker) require that their functional argument operate elementwise on arrays. This means for example that outer( 1:2, 3:4, list) or outer(1:2,3:4,function(a,b){1}) gives an error. Is there a version of `outer`/`kronecker`/etc. that takes arbitrary functions and does its own elementwise mapping? In the first example above, I'd expect the

Dear list, I'm stuck with looking for a function of the *apply family, which I suppose exists already ? just I can't find it: What I'm looking for is somewhere between sweep and mapply that does a calculation vectorized over a matrix and a vector: It should work complementary to sweep: for each row of the matrix, a different value of the vector should be handed over. Close to

Hola a todos: Se me ha planteado un problema que no está ligado a ningún problema concreto. Es más teórico. Supongamos que tenemos tres variables: V1 <- c (47, 71, 41, 23, 83, 152, 82, 8, 160, 18) V2a <- c (NA, 36, 15, 5, 56, 18, NA, 5, NA, 5) V2b <- c (37, NA, 15, NA, NA, NA, 90, NA, 161, NA) Supongamos que tengo la expresión (que no puedo asignarlo a

A ver... con que xfunc() esté preparada para tomar un parámetro de tipo "carácter" y evaluarlo, claro que se puede hacer... Si el problema lo tienes en evaluar la expresión, la función "eval()" te lo hace. Si no te he entendido bien, explícate más ? Saludos Isidro -----Mensaje original----- De: R-help-es <r-help-es-bounces en r-project.org> En nombre de Griera Enviado

Esta es la respuesta que te da ChatGPT-4: Entiendo tu pregunta y, aunque no hay una función nativa en R que te permita hacer exactamente lo que estás pidiendo, puedes lograr el mismo resultado utilizando una función. Una función te permitiría encapsular la lógica de la expresión que quieres reutilizar y luego llamar a esa función donde sea necesario. He aquí cómo podrías hacerlo: V1 <-

Muchas gracias, Manuel: Que bueno! No se me había ocurrido lo de GPT! Lo pruebo. Saludos. On Fri, 11 Aug 2023 18:15:18 +0200 Manuel Mendoza <mmendoza en fulbrightmail.org> wrote: > Esta es la respuesta que te da ChatGPT-4: > > Entiendo tu pregunta y, aunque no hay una función nativa en R que te > permita hacer exactamente lo que estás pidiendo, puedes lograr el mismo >

No tuve tiempo de mirarlo, pero, ¿es coherente lo que dice? El vie, 11 ago 2023 a las 21:02, Griera-yandex (<griera en yandex.com>) escribió: > Muchas gracias, Manuel: > > Que bueno! No se me había ocurrido lo de GPT! > > Lo pruebo. > > Saludos. > > On Fri, 11 Aug 2023 18:15:18 +0200 > Manuel Mendoza <mmendoza en fulbrightmail.org> wrote: > > >

Hi R-Group, I am stuck with the following problem: I am constructing a portfolio of 2 variables x and y x <- rnorm(100, mean=100, sd=4) y <- rnorm(100, mean=120, sd=10) which I am combining as follows to a portfolio for sampling purposes: portfolio <- c(rep(x, 8), rep(y, 2)) In this case I have assigned the weights of 8 and 2 to calculate the bootstrapped mean: mean.boot <-

I would like to give a probability distribution function of a function of (x,y) on the half-plane y>0, and a constant 0<c<1 and I would like to know the c percentile of the marginal distribution of x. I have tried along the lines of the following but I keep getting errors: # SIMPLIFIED PROBLEM # The plan is to solve for the .975 percentile "xc" of the marginal x distribution

Dear all, I am trying to learn lapply. I would like, as a test case, to try the lapply alternative for the Shadowlist<-array(data=NA,dim=c(dimx,dimy,dimmaps)) for (i in c(1:dimx)){ Shadowlist[,,i]<-i } ---so I wrote the following--- returni <-function(i,ShadowMatrix) {ShadowMatrix<-i} lapply(seq(1:dimx),Shadowlist[,,seq(1:dimx)],returni) So far I do not get same results

> From: Thomas Lumley > > On Sun, 30 Oct 2005, Jonathan Rougier wrote: > > > I'm not sure about this. Perhaps I am a dinosaur, but my feeling is > > that if people are writing functions in R that might be subject to > > simple operations like outer products, then they ought to be writing > > vectorised functions! > > I would agree. How about an

* What were your biggest misconceptions or stumbling blocks to getting up and running with R? * What documents helped you the most in this initial phase? I especially want to hear from people who are lazy and impatient. Feel free to write to me off-list. Definitely write off-list if you are just confirming what has been said on-list. -- Patrick Burns pburns at pburns.seanet.com