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https://github.com/dewittpe/ensr

Elastic Net SearcheR
https://github.com/dewittpe/ensr

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Elastic Net SearcheR

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# ensr: Elastic Net SearcheR

[![Build Status](https://travis-ci.com/dewittpe/ensr.svg?branch=master)](https://travis-ci.com/dewittpe/ensr)

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/ensr)](https://cran.r-project.org/package=ensr)
[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/ensr)](http://www.r-pkg.org/pkg/ensr)
[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/grand-total/ensr)](http://www.r-pkg.org/pkg/ensr)

Elastic Net regression models combine both the L1 and L2 penalties of lasso and
ridge regression. There are two penalty terms, lambda and alpha. Lambda is a
complexity parameter and alpha is a balance between lasso and ridge.

The `cv.glmnet` function in [`glmnet`](https://cran.r-project.org/package=glmnet)
will perform cross validation to find the value of lambda for a given value of
alpha. `cv.glmnet` does not search over values of alpha. The ensr package
builds a grid of alpha and lambda values and, using cross-validation, suggests
preferable values for both lambda and alpha.

After installing this package we encourage you to read the vignette to see
examples.

```r
vignette("ensr-examples", package = "ensr")
```

## Installing ensr

ensr is on [CRAN](https://cran.r-project.org/package=ensr).

```r
install.packages('ensr', repos = 'https://cran.rstudio.com')
```

Install the development version from github:

```r
if ('remotes' %in% rownames(installed.packages())) {
install.packages('remotes', repos = "https://cran.rstudio.com")
}
remotes::install_github("dewittpe/ensr", build_opts = c("--no-resave-data"))
```

## Development version from Github

There are several ways you can install ensr. If you are working on a Windows
machine you will need to have [Rtools](https://cran.r-project.org/bin/windows/Rtools/) installed.

### Clone and Install
There are detailed instructions for cloning the repo in the `CONTRIBUTING.md`
file. After cloning use the makefile to build, check, and install the ensr
package, e.g.,

make install

## Contributing
Please read the `CONTRIBUTING.md` file. There are details on the how to clone
the repo and the structure of this package.