similar to: remove higher order interaction terms

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

Dear R-help This is a follow-up to my previous post here: http://groups.google.com/group/r-help-archive/browse_thread/thread/d9b6f87ce06a9fb7/e9be30a4688f239c?lnk=gst&q=dobomode#e9be30a4688f239c I am working on developing an open-source automated system for running batch-regressions on very large datasets. In my previous post, I posed the question of obtaining VIF's from the output of

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

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?

Fellow R users, I'm using the BCE {BCE} function to run a Bayesian sediment mixing model. The aim is to find the optimum % contribution from each of the 4 source areas that can yield the target geochemistry. I have geochemistry for 4 source areas called Rat: Rat<-read.table(text="CaO MgO Na2O Al2O3 Topsoils 2.511250 0.7445500 0.7085500 14.10375 ChannelBanks

Hi Thierry, On 2 March 2016 at 10:16, Thierry Onkelinx wrote: | 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

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

Hola, No hace falta (en este caso) capturarlo de la consola. El resultado de la función apply se puede capturar y procesar. > data("mtcars") > # Mtcars_matriz <- as.matrix(mtcars) > res_out <- apply(mtcars, MARGIN =2, FUN = shapiro.test) > > > res_df <- as.data.frame(unlist(res_out)) > res_df$vars <- rownames(res_df) > rownames(res_df) <- NULL

I may have a deployment reason at work for Linux binary packages as created by `R CMD INSTALL --build src`. Using the example of my digest package this creates eg digest_0.6.18.1_R_x86_64-pc-linux-gnu.tar.gz where 'x86_64-pc-linux-gnu' is also what `R.version[["platform"]]` returns. However, once I started to look into supporting this via my repository helper package

If I understand you correctly, you want to have a mirror of CRAN on a private server behind your firewall. Check out https://cran.rstudio.com/mirror-howto.html <https://cran.rstudio.com/mirror-howto.html> which gives instructions on how to do this. Cheers, Rainer > On 8 Jun 2017, at 23:29, Joshua Bradley <jgbradley1 at gmail.com> wrote: > > Hello, > > I am trying to

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

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

> On Apr 15, 2016, at 1:16 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > 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

Greetings, I am interested in creating a stepwise fixed order regression function. There's a function for this already called add1( ). The F statistics are calculated using type 2 anova (the SS and the F changes don't match SPSS's). You can see my use of this at the very end of the email. What I want: a function to make an anova table with f changes and delt R^2. I ran into

> On Apr 16, 2016, at 2:03 AM, Akhilesh Singh <akhileshsingh.igkv at gmail.com> wrote: > > 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

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

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, 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

Bob Proulx wrote: > Here is a patch that I believe should fix the problem. I will also > attach it so that there won't be any mailer problems with the > transport of it. And I broke it in the editing of it. Drat! > + bridge=$(brctl show | | awk 'NR==2{print$1}') Which is obviously incorrect. Here is a hopefully correct patch. With only one pipe in the pipeline. ---