similar to: speeding up "sum of squared differences" calculation

grDevices::convertColor has arguments 'from' and 'to' which can take on value 'XYZ'. Can someone confirm that 'XYZ' is the same as the CIE chromaticity coordinates that are also sometimes refered to as 'xyY' in the literature? Or are these the CIE tristimulus values? It looks to me like the first case is true, but I would appreciate hearing from one of

Hi all, I have a very general question and I think for you maybe very easy, but I am not able to solve it. I have a dataset and that dataset contains the variable Anxiolytics. This variable is coded as 0, 1, 2. The variable looks as follows: > summary(DF$Anxiolytics) 0 1 2 NA's 1102 0 20 440 You can see that the variable is coded as 0, 1, 2, but group 1

Hola Estoy instalando R en una máquina con Linux Debian. Lo hago con la orden “apt-get install r-base r-base-dev” y me instala la versión 2.15.1 mientras que yo necesito algunos paquetes que solo funcionan con 3.0 en adelante (por ejemplo, Rccp). Gracias [[alternative HTML version deleted]]

I have would like to use logistic regression to analyze the percentage of correct responses in a 2 alternative forced choice task. The question is whether one needs to take into account the fact expected probabilities for the percentage of correct responses ranges between 0.5 and 1 in this case and how to adjust the link function accordingly in R (see details below). Gabriel Subjects were asked

Dear R-help, I posted this on 4 Oct but got no response (I wasn't even told to go away and do some more background reading ;) ). I am reposting it in the, perhaps, vain hope that someone with knowledge of the subject will reply, if only to point me in a different direction to which I am now facing. Earlier Posting:--- I am sorry if this is more of a stats question than an R-question, but I

Hi, I would have thought that these two constructions would produce the same result but they do not. Resp <- rbinom(10, 1, 0.5) Stim <- rep(0:1, 5) mm <- model.matrix(~ Stim) Xb <- mm %*% c(0, 1) ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) pnorm(as.vector(Xb), lower.tail = Resp, log.p = TRUE) > ifelse(Resp, log(pnorm(Xb)), log(1 - pnorm(Xb))) [1] -0.6931472 -1.8410216

Hi all. I started looking at Rcpp, which looks pretty great, actually. At the moment just trying to compile a module to get a feel how it all works without fully understanding how all the pieces fit together. Basically, i took the first example from Rcpp modules vignette: fun.cpp ======================== #include <Rcpp.h> #include <math.h> using namespace Rcpp; double

Has anyone plotted or is it possible to plot CIE *xy* chromaticity diagram http://en.wikipedia.org/wiki/File:CIE1931xy_blank.svg I need this plot in color. ishida [[alternative HTML version deleted]]

On Sat, Jan 28, 2023 at 2:49 PM Kenneth Knoblauch <ken.knoblauch at inserm.fr> wrote: > > Hi, > > I'm struggling to find if there is a simple way to make the lines and points overlap in a legend for a lattice plot using auto.key. Here is a toy example of what doesn't work (for me) as the lines and points are adjacent rather than overlapping: > > library(lattice)

Hi, I was taken off guard by the following behavior in a lattice plot. I frequently want to add a predicted curve defined at more points than in the formula expression of xyplot. There have been numerous examples of how to do this on r-help, but I still often struggle to make this work. I just realized that specifying one of the axes on a log scale does not guarantee that the added data for a

Dear R experts, Did someone implemented French Curve yet? Or can anyone point me some papers that I can follow to implement it? thanks in advance for your help. Paul

Hi, I'm struggling to find if there is a simple way to make the lines and points overlap in a legend for a lattice plot using auto.key. ?Here is a toy example of what doesn't work (for me) as the lines and points are adjacent rather than overlapping: library(lattice) d <- data.frame(x = 1:2, y = 1:4, f = factor(letters[1:2])) xyplot(y ~ x, d, groups = f, type = "b",? pch =

I've never seen anything written about multiple comparisons, as in the multcomp package or with TukeyHSD, but using a glm. Do such procedures exist? Are they sensible? Are there any packages in R that implement such comparisons? Thank you. -- Ken Knoblauch Inserm U371 Cerveau et Vision 18 avenue du Doyen Lepine 69675 Bron cedex France Tel: +33 (0)4 72 91 34 77 Fax: +33 (0)4 72 91 34 61

Hi! Is it possible to easily cut & paste data from an Excel spreadsheet to an R edit( ) grid or to variable? It seems that R cannot handle the cell delimiters Excel hands over. Regards, Werner

I'm using scan in a script to record a series of responses of the user as a function of some graphs that I put up on the screen. A toy version would be, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } However, if I include any code after this loop, for example, y <- rep(NA, 3) for (ix in seq( length(y) ) ) { y[ix] <- scan( n = 1 ) } y I get an error

I'm having a problem with dotted lines (lty = 3) in the pdf output in documents generated with Sweave. In the displayed pdf, the dotted line does not show up and in the printed output, it is there but does not seem to respect the lwd argument, for example, it is very faint despite using lwd = 3. The dotted line is correct in a quartz window and if I save the Quartz window to a pdf and

Hi there are some predefined self-start functions, like SSmicmen, SSbiexp, SSasymp, SSasympOff, SSasympOrig, SSgompertz, SSflp, SSlogis, SSweibull, Quadratic, Qubic, SSexp (nlrwr) Btw, do you know graphic examples for this functions? The SSexpDecay (exponential decay) for y = (y0 - plateau)*exp(-k*x) + plateau from

Your response nicely clarifies a question that I've had for a long time, but which I've dealt with by giving each subject a unique label. Unless I'm missing something, both techniques should work as the toy example below gives exactly the same output in all 3 cases below (forgetting about the convergence problem). Would there be a reason to prefer labeling the levels one way or

Dear all, I would like to generate 25 numbers from 1 to 100 but I would like to have some numbers that could be more probable to come out. I was thinking of the function runif: runif(25, 1, 100) , but I don?t know how to give more weight to some numbers. Example: each number from 2 to 10 has the probability of 40% to come out but the probability of each number from 11 to 100 to come out is

Sorry, some things got garbled in that request for help that might make my request unintelligible, probably it being too late at night when I posted, here is the corrected function call for which I would like to learn how to add horizontal grid lines. Any suggestions would be appreciated. Apologies for the posting error xyplot(est ~ STE, data = all, groups = AREA, type = "b",