Re: [R] Possible solution to R installation problemst for Linux Mint 19 users

2018-07-21 Thread Jeff Newmiller
Each Mint version builds from an Ubuntu version. I don't use Mint. but this [1] web page tells me you should be pulling from a Bionic repo. Artful may work for you now, but in general it is risky to mix distribution revisions. Note that this informative discussion should have occurred on the

[R] Possible solution to R installation problemst for Linux Mint 19 users

2018-07-21 Thread Clive Nicholas via R-help
Hello! If you're a newly-minted (pun _fully_ intended) user of Linux Mint 19 ("Tara") and you find you're having issues installing R (as I just have), please read on as I may have a solution for you. To set out the context, the problem looks like this: You (naturally) consult the relevant

Re: [R] (no subject)

2018-07-21 Thread Rui Barradas
Hello, Please always write to r-help, not to me personally, even if I was able to be of assistance in the past. As for your question, your code has several problems. 1) rowSums and colSums return vectors, not matrices. Even if they did, see point 3) below. 2) You define K = 0 then in

Re: [R] Problem with mean()

2018-07-21 Thread Jeff Newmiller
Read ?mean. Look at the argument list. The mean function only applies to the first argument. On July 21, 2018 9:39:42 AM PDT, John Kane via R-help wrote: >Either I am doing something very stupid or my R installation has a >glitch. What am I missing? >dd1  <- 50 >dd2  <- 54 > >mean(dd1, dd2)

Re: [R] Problem with mean()

2018-07-21 Thread Duncan Murdoch
On 21/07/2018 12:39 PM, John Kane via R-help wrote: Either I am doing something very stupid or my R installation has a glitch. What am I missing? dd1  <- 50 dd2  <- 54 mean(dd1, dd2) [1] 50  # wrong Read the help page ?mean. You are specifying the parameters x and trim. Duncan Murdoch

Re: [R] Problem with mean()

2018-07-21 Thread Rui Barradas
Hello, The first argument of mean is a vector, the dots argument is to be "passed to or from other methods." (from ?mean) Try instead mean(c(dd1, dd2)) Hope this helps, Rui Barradas Às 17:39 de 21-07-2018, John Kane via R-help escreveu: Either I am doing something very stupid or my R

[R] Problem with mean()

2018-07-21 Thread John Kane via R-help
Either I am doing something very stupid or my R installation has a glitch. What am I missing? dd1  <- 50 dd2  <- 54 mean(dd1, dd2) [1] 50  # wrong (dd1 + dd2)/2 [1] 52 # correct aa  <- c(48, 52, 56, 54, 52) mean(aa) [1] 52.4 # correct [[alternative HTML version deleted]]

Re: [R] Install BMR package - Mac

2018-07-21 Thread Jeff Newmiller
Agree with Bert, but Google sez [1] might also be helpful. [1] https://github.com/Microsoft/LightGBM/issues/3 On July 21, 2018 7:28:55 AM PDT, Bert Gunter wrote: >As this appears to be a Mac specific issue, if you don't get help here, >you >should try posting on the r-sig-mac list. Maybe even

Re: [R-es] Lanzar R desde Shiny server

2018-07-21 Thread Javier Marcuzzi
Estimado Jesús Para Fernández Creo que no, porque R fue creado para comenzar, calcular, dar el resultado, y finaliza, lo que usted pretende es algo que escuche todo el tiempo, y si en ese tiempo sucede algo, ese algo le ordena a R comenzar su calculo y dar el resultado, luego lógicamente se

Re: [R] Install BMR package - Mac

2018-07-21 Thread Bert Gunter
As this appears to be a Mac specific issue, if you don't get help here, you should try posting on the r-sig-mac list. Maybe even better would be to contact the maintainer of the BMR package, who might not monitor either list. Cheers, Bert Bert Gunter "The trouble with having an open mind is

[R] Install BMR package - Mac

2018-07-21 Thread Beatrice Monti
Hi all, I am having problems installing the BMR package. I have been trying the following: install.packages("devtools”) library(devtools) install_github("kthohr/BMR") This is the error I get: clang: error: unsupported option ‘-fopenmp' I have dowloaded and

[R] Fwd: Re: scatter plot coloring problem

2018-07-21 Thread Micha Silver
Hi On 07/20/2018 03:16 PM, PIKAL Petr wrote: Hi Values in conv_df are almost same for each Error level Thanks to Petr for help in catching this! aggregate(conv_df$Intercept, list(conv_df$Error), mean) Group.1 x 1 High CML error -3.226313 2 Low CML error -3.226536 3