HoRM VS polished_example_apps

Compare HoRM vs polished_example_apps and see what are their differences.

HoRM

Supplemental Functions and Datasets for "Handbook of Regression Methods" (by dsy109)
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HoRM polished_example_apps
1 1
0 30
- -
7.3 1.7
9 months ago about 1 year ago
R R
- -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

HoRM

Posts with mentions or reviews of HoRM. We have used some of these posts to build our list of alternatives and similar projects.

polished_example_apps

Posts with mentions or reviews of polished_example_apps. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-02-16.
  • Securing R Markdown Documents
    4 projects | /r/rstats | 16 Feb 2022
    You aren't able to load an entirely different .Rmd, but depending on the user's credentials (Admin v. non-Admin, user roles, login email), you can render (or not render) particular elements or even chunks of elements. Below is a modified version of our minimal polished::secure_rmd example app here.

What are some alternatives?

When comparing HoRM and polished_example_apps you can also consider the following projects:

mindr - an R package which converts markdown files (.md, .Rmd) into mindmaps (brainstorms)

electricShine - Create Standalone Installable Shiny Apps

future - :rocket: R package: future: Unified Parallel and Distributed Processing in R for Everyone

flexdashboard - Easy interactive dashboards for R

easystats - :milky_way: The R easystats-project

polished - Authentication and Administration for Shiny apps

ggstatsplot - Enhancing {ggplot2} plots with statistical analysis 📊📣

forecast - Forecasting Functions for Time Series and Linear Models