In the same R session, change the working directory to the new location above: setwd("/path/to/application_directory/pmp_cid_app").In this R session, run the following command: packrat::unbundle("/path/to/pmp_cid_", "/path/to/application_directory") where /path/to/application_directory is the app_dir configured for Shiny Server. Launch a new R session on the Shiny server.After some time, a new file called pmp_cid_ should be present in the same directory. Create a bundle of the application by executing this R command: packrat::bundle().Once R completes initialization, a message should appear that this is a packrat-enabled project. Launch R in the same directory with the clone of the repository.Refer to the separate document for instructions on cloning the repository. Clone the application's repository to any local directory that is outside of the Shiny Server's application source directory.To deploy this application, the server administrator will need to follow this procedure: For complete details on administering Shiny Server, please refer to the Administrator's Guide. Since the application utilizes more R packages besides Shiny, the R package installed on the default R library for the server. The application is construction with the R statistical computing language (version 3.6.0), and the Shiny package is used to create the application's web interface. The following pre-requisites must be fulfilled in order to access and use the application: Compute Environment A separate document with complete instructions on accessing and downloading the contents of this repository will be supplied to all collaborators on this project. This document outlines the general procedure for deploying and using the Shiny application. (Note that the application reference in this template depended on key analytical libraries that are likely out of scope for our pilot submission) In the North American deserts fossil packrat midden analysis has. Below is an excerpt from the repository I created for the particular project which we can adapt to our needs. Packrat Middens: The Last 40,000 Years of Biotic Change. I have tried this once before with the Complex Innovative Designs (CID) initiative in partnership with FDA. The following is a list of the R functions in the packrat package that you’ll use most often.
#PACKRAT R INSTALL#
A critical part of the pilot 2 submission is the documentation that covers how a reviewer can successfully install the app package and run it locally on their R installation.
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