similar to: Best way to handle dependency on non-CRAN package / large data package?

Hi Dirk, I'm interested in pursing this but I haven't been able to figure how to to make it work. Here's what I have so far: install.packages("drat") library(drat) addRepo("arilamstein") I (obviously) have a copy of the choroplethrZip github repo locally. I typed: git checkout gh-pages git push I gather that this is what I needed to to do make the repo

Thanks Dirk. I'm looking at it now. At first glance your documentation brings up a good limitation of simply telling users to type "devtools::install_github()". Namely, what happens when the census bureau updates their shapefiles, and I subsequently decide to update the package? Or if I discover an error in the package and decide to update it? The choroplethr package could have a

On 12 March 2015 at 09:40, arilamstein at gmail.com wrote: | Thanks Dirk. I'm looking at it now.? | | At first glance your documentation brings up a good limitation of simply | telling users to type "devtools::install_github()". Namely, what happens when | the census bureau updates their shapefiles, and I subsequently decide to update | the package? Or if I discover an error in the

On 12 March 2015 at 08:41, arilamstein at gmail.com wrote: | But I don't know if this is the best way to do this, or if there is | anything else to consider. I have never had to manage package dependencies | outside of CRAN, and have always thought of CRAN as being a "closed | ecosystem", where there were not any dependencies outside of CRAN. | | Can anyone provide guidance on this?

Dear all, Consider the model below: > x <- lm(mpg ~ cyl * disp * hp * drat, mtcars) > summary(x) Call: lm(formula = mpg ~ cyl * disp * hp * drat, data = mtcars) Residuals: Min 1Q Median 3Q Max -3.5725 -0.6603 0.0108 1.1017 2.6956 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.070e+03 3.856e+02 2.776 0.01350 * cyl

I have applied the same linear model to several different subsets of a dataset. I recently read that in R, code should never be repeated. I feel my code as it currently stands has a lot of repetition, which could be condensed into fewer lines. I will use the mtcars dataset to replicate what I have done. My question is: how can I use fewer lines of code (for example using a for loop, a function or

Dear R People: I have a data frame, xm1, which has 12 rows and 4 columns. If I put is xm1[,-4], I get all rows, and columns 1 - 3, which is as it should be. Now, is there a way to use the names of the columns to omit them, please? Thanks so much in advance! Sincerely, Erin -- Erin Hodgess Associate Professor Department of Computer and Mathematical Sciences University of Houston - Downtown

Dear all, install.packages("lme4") fails with error Error in read.dcf(file = tmpf) : cannot open the connection In addition: Warning message: In read.dcf(file = tmpf) : cannot open compressed file '//servername/repository_path/bin/windows/contrib/3.2/PACKAGES', probable reason 'No such file or directory' the repositories set in .Rprofile are

Dear Sirs, I am Professor at Indira Gandhi Krishi Vishwavidyalaya, Raipur, Chhattisgarh, India. While taking classes, I found the *by() *function producing following error when I use FUN=mean or median and some other functions, however, FUN=summary works. Given below is the output of the example I used on a built-in dataset "mtcars", along with error message reproduced herewith: >

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # extract un-rotated scores of

I think you are not using the best function for what your intentions are. Try: > by(data=mtcars, INDICES=list(as.factor(mtcars$am)), FUN=colMeans) : 0 mpg cyl disp hp drat wt qsec vs 17.1473684 6.9473684 290.3789474 160.2631579 3.2863158 3.7688947 18.1831579 0.3684211 am gear carb 0.0000000

Hello, I am trying to setup a private CRAN for work (behind a firewall). The best options available include miniCRAN <https://github.com/RevolutionAnalytics/miniCRAN>, drat <https://github.com/eddelbuettel/drat> and packrat <https://rstudio.github.io/packrat/>. One problem is these packages do not automatically generate the web pages that are on the CRAN. Examples:

Dear All, Thanks for your help. However, I would like to draw your attention to the following: Actually, I was replicating the Example 2.3, using the dataset "brainsize.txt" given in Section 2.3.3 ("Summarize by group") at page 55, of a famous book "R by Example" written by "Jim Albert and Maria Rizzo" published in Springers (2012) in a Use R! Series. The

Buen día estimados Estoy tratando de hacer un tibble con los resultados de un apply que se muestran en la consola que me da R, no estoy seguro si eso se pueda hacer, pero me gustaría organizar los resultados de esa manera. mi código es: data("mtcars") Mtcars_matriz <- as.matrix(mtcars) apply(Mtcars_matriz, MARGIN =2, FUN = shapiro.test) DF2 <- tibble(Variable = NA, W = NA, Pvalue =

Hi, I'm a novice of R. I want to read the following table into R: names mpg cyl disp hp drat Mazda RX4 21.0 6 160.0 110 3.90 Mazda RX4 Wag 21.0 6 160.0 110 3.90 The command I used is: > test <- read.table(file.choose(),header=T) The result is: Error in read.table(file.choose(), header = T) : more columns than column names

Hola, Bueno, puedes hacer el cálculo de una forma mucho más compacta y rápida. Esta forma es especialmente recomendable cuando tienes muchas columnas y muchas filas. > library(data.table) > myDT <- as.data.table(mtcars) > myDTlong <- melt(myDT, measure.vars=1:ncol(myDT)) > myDTlong[ , list(p_value = shapiro.test(value)$p.value, v_stat = shapiro.test(value)$statistic) , by

Fraunhofer Institute for Integrated Circuits has stopped providing licenses for MP3 technology, "[...] noting that more superior audio formats have rendered the MP3 obsolete. Speaking to National Public Radio (USA), the Fraunhofer Institute said AAC has since become the 'de facto standard for music download and videos on mobile phones.' "

Dear list, I want the 1st, 2nd, 5th, and 6th columns of mtcars. After copying them, the columns become numeric class rather than data frame. But, when I copy rows, they data frame retains its class. Why is this? I don't see why copying rows vs columns is so different. > class(mtcars) [1] "data.frame" > head(mtcars) mpg cyl disp hp drat wt qsec vs

Dear All, I have got your core message, that it is my responsibility to determine whether any particular function in my version of R satisfies the language requirements at the time of your use. Jim Albert and Maria Rizzo must have used their code, which was permitted in the R-code of their time (2012). Therefore, I have now modified my R-code, as per R-3..2.4 version, according to my requirement

On Wed, Jul 28, 2010 at 9:01 AM, David Piepgrass <dpiepgrass at mentoreng.com> wrote: >> A LLVM JIT compiler for x86 under 1 MB? I doubt it is possible without >> a major rewriting of LLVM. > > Even with no optimizations? Drat. That means I can't use it. Why? I'd never checked, but I always assumed the LLVM JIT was much larger than 3.4 MB. For comparison: [rnk at