Just to bring it back to R, I want to point out that what many R programmers do
is not that different. If you develop some skills at analyzing some kinds of
data and have a sort of toolchest based on past work, then a new project along
similar lines may move very quickly. After a while, you
Fixed!
I was not passing a tol value from the outer function to the inner
qnbinom() function. Because the scope of tol in qbinom() was confined to
the outer function, qnbinom was not accessing the globally defined tol
value. Furthermore, because the outer function itself was embedded in
Jim,
I am not sure what your example means but text to image conversion can be
done quite easily in many programming environments and does not need an AI
unless you are using it to hunt for info. I mean you can open up many Paint
or Photo programs and look at the menus and often one allows you
The dredge function has a `extra` argument to get other statistics:
optional additional statistics to be included in the result, provided as
functions, function names or a list of such (preferably named or
quoted). As with the rank argument, each function must accept as an
argument a fitted
The near year as Metropolis, 1927.
On Tue, Jul 18, 2023, 1:27 AM Rui Barradas wrote:
> Às 00:23 de 18/07/2023, Jim Lemon escreveu:
> > I haven't really focused on the statistical capabilities of AI, that
> > marriage of massive memory and associative learning. I am impressed by
> > its ability
A repost.
R gurus:
I have a 10 or so functions that use R’s qnbinom() function. Until now,
they have worked without any problems whatsoever.
I created a new function, which involved the integration, using R’s
integrate(), of a function that in turn uses the qnbinom() function.
The function failed
В Tue, 18 Jul 2023 09:28:30 -0400
Joseph Lucke пишет:
> Error in qnbinom(1 - tol, size = q, prob = r) :
> pRsq.Rhosq <- function(x, n, p, Rhosq,tol=tol){
It looks like you're not passing the `tol` parameter, and its default
value unfortunately refers to itself:
(function(x = x) x)()
# Error
On Wed, 1 Apr 2015, Prof Brian Ripley wrote: I would start by trying
LANGUAGE=en , e.g. More specifically, you can use en_US or en_GB. Rich [...]
͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏
> I am not sure what your example means but text to image conversion can be
> done quite easily in many programming environments and does not need an AI
> unless you are using it to hunt for info. I mean you can open up many Paint
> or Photo programs and look at the menus and often one allows you
Hadley,
Thanks and I know many such things exist. I simply found it interesting that
what was mentioned seemed simpler as just being a converter of text to make a
bitmap type image. Now if I want a simulated image of a cat riding a motorcycle
while holding an Esperanto Flag, sure, I would not
I was thinking that text-to-image conversion was something like NightCafe
(https://creator.nightcafe.studio/) which is very much AI and not something I
know how to do with Paint or Photoshop.
-Original Message-
From: avi.e.gr...@gmail.com
Sent: Tuesday, July 18, 2023 2:34 PM
To: 'Jim
Buenas, Yesica:
La variable iteraccion parece una variable factor, en cuyo caso ¿no se debería
incluir en el anova? en vez de repetir muchas veces el anova.
Si se trata de repeticiones también hay modelos anova con repeticiones.
En tu código estás haciendo el mismo anova muchas veces pues no
Buenos días y gracias de antemano por vuestra ayuda.
Necesito realizar una serie de ANOVAS en loop.
Os adjunto unos datos ficticios en este email.
Dichos datos tienen 3 variables:
1)Valor: corresponde a la variable dependiente y es numérica
2) Grupo: Corresponde a la variable independiente y es u
Holaotra opción, a ver si te sirve.Acabarás teniendo 6 archivos txt y 6
archivos xlsx cada uno con el resultado de cada una de las iteraciones.
library(purrr)library(broom)
iter= unique(datos$iteraccion)#Crear el loopfor(i in iter) {
a<-tidy(aov(valor~Grupo,data=subset(datos,
Hola Yésica,
A lo mejor hay otras formas, pero esta funciona bien:
R> u <- unique(datos$iteraccion)
R> resultado <- lapply(u, function(i){
aov(valor ~ Grupo, data = subset(datos, iteraccion == i))
})
R> names(resultado) <- u
Para acceder a la tabla ANOVA para iteraccion T simplemente haces
>
Hola,
library(dplyr)
library(purrr)
library(tidyr)
datos_anova <- datosa_fict |>
nest(data = c(valor, Grupo)) |>
mutate(anova = map(.x = data,
.f = ~aov(valor ~ Grupo, data = .x)),
summary = map(.x = anova, .f = ~summary(.x)))
# Acceder a los resultados
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