## Background and Project Goals

The world needs a statistical tool that is valuable both for teachers and practitioners. Many of the statistical tools in use today are highly expensive, proprietary, and carry a large amount of baggage. Many tools can’t be reasonably automated. Tools that can be automated (often written in R, Python, Java, and other languages) are incomplete from both a teaching and working standpoint.

The main objective of this project is to provide a tool set that is accurate, reliable, efficient (for the end user), and provides enough additional functionality to be valuable above and beyond many of the commercial tools in existence today. Ideally, users of this tool should not need to be proficient developers. In fact, using the code samples included in the online package documentation along with a couple of small sections of my tutorial on R, practitioners and students (at all levels) should not really need to know much at all in terms of R.

You’ll find something useful in this package regardless of whether you are a student just starting your journey or an experienced practitioner analyzing large amounts of data.

## Cost to Use the Package

The public release of the package itself is offered free of charge and is open source. You are free to take it and modify it any way that you choose.

The online documentation is not included under the open source license and may not be redistributed or stored without express written consent; however it is free to access online anytime.

See the LICENSE file in the package or on github for more details on the license.

Reasonably, if you are working on behalf of a commercial entity and you are using the package in a significant capacity, please support the project with a donation (contact me for more details). Also, if you find that you would like paid support and/or feature development, please contact me for more details.

## Where to Obtain the Package Source

If you want to browse the package source, see the official github location:

https://github.com/burrm/lolcat

## Installing the Package

Make sure that you have the following installed:

• R
• RStudio

The easiest way to install the latest package version is to use devtools and run the following R script:

# Install the devtools package
install.packages("devtools")

require(devtools)

install_github("burrm/lolcat")

require(lolcat)

If the package is successfully loaded, you will likely see something like this:

> require(lolcat)
>

### Notes for System Administrators (Most People Can Skip This)

System administrators seeking to install the package system wide (o.e. for all users) should install the package in the “site” package directory or use a network location for shared packages.

• Windows: C:Files-{version}
• Linux: Varies…
• On the latest Fedora Core Release, the site package directory is /usr/lib64/R/library/. I’d expect this to be the same for other Redhat/CentOS variants using yum/dnf for package management.
• On the latest Ubuntu release, the site package directory is /usr/lib/R/library/. I’d expect the same for other Debian/Ubuntu variants using apt for package management.
• If you build R yourself or use a non-standard distribution, you’re your own best hope to locate the site package directory.
• Mac OS: Someone will have to tell me…

TODO

TODO

TODO