If you have a large dataset (ex: 170 000 cases, 13 features) and you are using the default parameter fDet="T", you could need 122G RAM after LM & GM! This problem is located in the plotting sections of the other methods.

See http://r-pkgs.had.co.nz/data.html

The RRegrs tutorial is ready to be included in RRegrs package as vignette
https://www.overleaf.com/1464339xbzznq#/3643091/

Hi

Thanks for the nice package.

I wonder whether you plan to submit to CRAN in the near future? As far as I can see, it is not currently available from there? (So, I think it can currently only be installed via downloading the ZIP?)

Richard

Let's stick to 1st column being y, with no specific col name.

Hi,

I'm trying to use RRegrs to perform full training on training samples and I'd like to use it to validate the results on a specific test set I have. I have two data frames train.df and test.df, I renamed the first column of each one of them to net.c, otherwise it wouldn't work, but when I run:

RRegrs::LMreg(train.df,test.df,sCV="none")

I get an error:

Error in $<-.data.frame(*tmp*, "method", value = "lm") : replacement has 1 row, data has 0

By inspection, I noticed this happens because since I set sCV to none, it is full training therefore lm.fit$results returns an empty data.frame. The metrics RMSE and R2 would have to be calculated manually using caret::RMSE and caret::R2 in this case.

repeatedCV is.

As it is now, the user has to create a DataResults folder and copy the dataset to it by himself, which is not very user friendly. I suggest that this is done automatically when calling the RRegrs function.

When trying to install RRegrs (R 3.1.3) there seems to be a problem with doMC dependency. The error says doMC is not available as a binary (which is true http://cran.r-project.org/web/packages/doMC/index.html).

Copied from https://github.com/muntisa/RRegrs/issues/1.

iSCalCol=2 is supposed to only scale the features.

Hello, I'm a reader of your paper published on the JCheminformatics
I want to try to use this library
Can you provide some tutorial or example file such as the applications presented in the paper?
I think it will be very useful to provide that and encourage beginners to use this tool
Thanks

install.packages("devtools")
install.packages("gtable")
install.packages("scales")
install.packages("iterators")
install.packages("stringr")
install.packages("brglm")
install.packages("gtools")
install.packages("lme4")
library("devtools")
install_version(package='caret',version='6.0-52')

install.packages("snow")
install.packages("lars")

Hi All,

When I install, I get the erro information like this:

Error in unloadNamespace(package) :
namespace ‘Rcpp’ is imported by ‘scales’, ‘reshape2’, ‘plyr’, ‘minqa’ so cannot be unloaded
Error in library(pkg, character.only = TRUE, logical.return = TRUE, lib.loc = lib.loc, :
Package ‘Rcpp’ version 0.12.2 cannot be unloaded
ERROR: lazy loading failed for package ‘RRegrs’

• removing ‘/Users/fuxianjun/Library/R/3.2/library/RRegrs’

How can I resolve it?

Any advice would be greatly appreciated.

Xianjun

library(devtools)
install_github("enomapper/RRegrs", subdir = "RRegrs") gave the following output:

Downloading GitHub repo enomapper/RRegrs@master
Error in download(dest, src, auth) : client error: (404) Not Found

Downloaded RRegrs-0.0.5.tar.gz into my home folder and ran in R 3.2.2 the following:

install.packages("RRegrs-0.0.5.tar.gz", repos = NULL, type = "source") gave:

Installing package into ‘/home/nathan/R/x86_64-pc-linux-gnu-library/3.2’
(as ‘lib’ is unspecified)
Warning in untar2(tarfile, files, list, exdir, restore_times) :
skipping pax global extended headers
ERROR: cannot extract package from ‘RRegrs-0.0.5.tar.gz’
Warning in install.packages :
installation of package ‘RRegrs-0.0.5.tar.gz’ had non-zero exit status

The alternative method of running R CMD routine also failed.

Solving a lot of warnings, like:

* checking whether package ‘RRegrs’ can be installed ... WARNING
Found the following significant warnings:
  Warning: replacing previous import by ‘pls::R2’ when loading ‘RRegrs’

E.g.:

bibentry(bibtype = "Manual",
title = "{nlme}: Linear and Nonlinear Mixed Effects Models",
author = c(person("Jose", "Pinheiro"),
person("Douglas", "Bates"),
person("Saikat", "DebRoy"),
person("Deepayan", "Sarkar"),
person("R Core Team")),
year = year,
note = note,
url = "https://CRAN.R-project.org/package=nlme")

See https://cran.r-project.org/doc/manuals/r-release/R-exts.html#CITATION-files

(feedback from paper reviewer)