How to Install Rgogo
This article outlines the system requirements and how to install Rgogo.
Rgogo is cross-platform.
Rgogo runs in R programming environment. Since R can be installed in Windows, macOS or Linux, so is Rgogo.
Running Rgogo requires R version 4.0.0 or above.
To install or update R, visit https://cran.r-project.org
In addition to R environment, we also recommend installing RStudio. RStudio is a software tool that proveds an integrated development environment for R users. RStudio desktop edition is an open-source software. It can be freely downloaded and installed in Windows, macOS or Linux, depending on which operating system you are using.
To download or update to the latest version of RStudio, visit https://rstudio.com
To install Rgogo package, follow the following steps:
devtoolspackage by entering the following command in R console:
Installation of Rgogo requires
devtools package. If you have not installed
devtools, you will encounter an error message like below:
1Error in library(devtools) : there is no package called 'devtools'
In this case, you should install
devtools first, and then attach the package:
Rgogopackage. This is done by entering the following command in R console:
1install_github(repo = "ActPersp/Rgogo")
install_github command will download and install Rgogo package from GitHub.
During the course of Rgogo installation, the process will also automatically install several other packages that Rgogo depends on if they have not been installed in your local R library.
After the installation process is completed, you can try attaching Rgogo package to see if it has been installed successfully.
If the installation is successful, you should not see any error message after the execution of the above command.
The level of R experience required by Rgogo depends on how you will use the package.
Simply using Rgogo to build and run a typical actuarial model does not require a modeler to be a professional R developer. A moderate level of R experience should be sufficient.
If you intend to extend or customize Rgogo functions extensively to meet your modeling needs, more advanced knowledge in R will be needed. In particular, a good understanding of the R object-oriented programming S4 class system will be essential.
This webiste assumes that you already have the necessary R skills for using Rgogo in your modeling work. Do not feel intimidated if that is not the case. There are many books and internet resources that can help you to learn R. Learning R is rewarding because the knowledge will benefit you beyond using Rgogo.