/WeibullR.shiny

A Shiny App for Weibull Analysis from WeibullR

Primary LanguageRApache License 2.0Apache-2.0

WeibullR.shiny

CRAN status CRAN checks Lifecycle:experimental

Introduction

Welcome to WeibullR.shiny, a Shiny web application for life data analysis based on the WeibullR package in R. This app has an intuitive interface for performing Weibull analysis, making it accessible for users with varying levels of experience.

Getting Started

To install WeibullR.shiny in R:

install.packages("WeibullR.shiny")

To install the development version:

devtools::install_github('paulgovan/weibullr.shiny')

To launch the app:

WeibullR.shiny::WeibullR.shiny()

Or to access the app through a browser, visit paulgovan.shinyapps.io/WeibullRshiny.

Example

Landing

Upon launching the app, you’ll be greeted by the Landing page. From here, you can:

  • Access this README.
  • Download an example dataset.
  • Navigate to the Data tab.

Data

For demonstration, we’ll use the “Time-to-Failure” dataset. First, download the dataset from the Landing page. Then, use the Data Input option in the Data tab to upload it to the app.

At this stage, your app should resemble the following:

You can explore additional options for data arrangement, but for this example, we’ll proceed with the default settings.

Modeling

Next, navigate to the Modeling tab to build your Weibull model. The app will generate a Probability Plot using default settings. Feel free to experiment with different configurations to tailor the model to your needs.

Below the plot, you’ll find additional settings for further customization.

Finally, visit the Contour Plot tab to create a contour plot. As with the previous plot, various customization options are available.

Code of Conduct

Please note that the WeibullR.shiny project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

More Resources

WeibullR.plotly is a package for building interactive Weibull models.

WeibullR.learnr is an interactive introduction to life data analysis.