similar to: Getting Rd pages right for redefined S3 generic

Dear R List, I have found that R handles a remarkable number of analytic tasks that are overlooked by major commercial packages. However, I have not found an R package that handles MaxDiff Scaling - does one exist? Thanks in Advance, Stephen Brand

All, I am using a sum of squared differences in the objective function of an optimization problem I am doing and I have managed to speed it up using the outer function versus the nested for loops, but my suspicion is that the calculation could be done even quicker. Please see the code below for a simple example. If anyone can point out a faster way I would appreciate it greatly. Thanks, Roger

Hi all, I've noticed that many computational neuroscience research groups use MATLAB. While it's possible that MATLAB may have some features unavailable in R, I suspect that this may instead simply be a case of costly tradition, where researchers were taught MATLAB as students and pay for it as researchers because it's all they know. I'd like to attempt to break the cycle by

CRAN (and crantastic) updates this week New packages ------------ Updated packages ---------------- New reviews ----------- This email provided as a service for the R community by http://crantastic.org. Like it? Hate it? Please let us know: cranatic at gmail.com.

I was working on a permutation-like variant of the bootstrap for smaller samples, and wanted to be able to get summary stats of my estimator conveniently. mean() is OK as its a generic, so a mean.oddboot function gets used automatically. But var, sd and others are not originally written as generic; they have to be explicitly masked by a package or new declaration. It would have been nice if

New packages psyphy and MLDS are available on CRAN: psyphy ncludes an assortment of functions useful in analyzing data from pyschophysical experiments. It includes functions for calculating d' from several different experimental designs, links for mafc to be used with the binomial family in glm (and possibly other contexts) and selfStart functions for estimating gamma values

New packages psyphy and MLDS are available on CRAN: psyphy ncludes an assortment of functions useful in analyzing data from pyschophysical experiments. It includes functions for calculating d' from several different experimental designs, links for mafc to be used with the binomial family in glm (and possibly other contexts) and selfStart functions for estimating gamma values

Hi, how can I replace NA value with 0: 1991 217 119 103 109 137 202 283 240 146 NA 1992 270 174 149 144 166 239 278 237 275 NA 1993 146 111 104 89 98 131 153 148 175 NA 1994 177 123 146 124 121 200 266 191 240 106 1995 145 98 95 89 95 130 183 161 164 129 1996 145 98 89 90 93 138 158 131 161 161 1991 217 119 103 109 137 202 283 240 146 0 1992 270 174 149 144 166 239 278 237

I fully agree, Michael, that this would be a great thing to have! I have often wondered why R and the standard packages are still sticking so much to the old-style S3 flavor though S4 is part of standard R. I acknowledge that backward compatibility is important, but, as far as I got it, redefining a function or S3 generic as an S4 generic should not harm existing functionality (if done

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, 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

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]]

Dear list, It seems that S4 methods defined for an S3 'base' generic are not used in 'base' functions. This can be problematic when 'base' functions start with something like 'as.matrix'. ### START R code setClass("classA", contains = "matrix", representation(realData = "numeric")) setMethod("as.matrix",

On 03/27/2014 02:13 AM, Ulrich Bodenhofer wrote: > I fully agree, Michael, that this would be a great thing to have! I have > often wondered why R and the standard packages are still sticking so > much to the old-style S3 flavor though S4 is part of standard R. I > acknowledge that backward compatibility is important, but, as far as I > got it, redefining a function or S3 generic as

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

I have grades data. I read them from a csv in letter-grade format. I then converted them to levels levels(grades$grade)=c('A+','A','A-','B+','B','B-','C+','C','C-','D+','D','D-') And then to numbers grades$gp=grades$grade levels(grades$gp)=c(4.3,4.0,3.7, 3.3,3.0,2.7, 2.3,2.0,1.7, 1.3,1.0,0.7)

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 =

Dear R friends I wanted a function to make a simple percent table that would be easy for students to use. The goal originally was to have a simple thing people would call like this pctable(rowvar, colvar, data) and the things "rowvar" and "colvar" might be names of variables in data. I wanted to avoid the usage of "with" (as we now see in the table help). Then