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quantrra's Introduction

{quantrra}

{quantrra} is a package for reproducible risk assessment developed for the statistical software R.

Installing quantrra

You can install quantrra development version from GitHub using the following code in your R console (make sure you have R > 3.5):

# make sure you have the package devtools installed
devtools::install_github('spablotemporal/quantrra')

Getting started

quantrra was developed for the implementation of stochastic risk assessment models as an open access alternative to software such as @Risk. quantrra provides a set of functions to be used in R, and also offers a more user friendly interface trough shiny that can be accessed using:

quantrra::run_quantrra()

Main usage

The main usage for quantrra is to simulate stochastic events using the function ra_run(), which requires two arguments:

  • m, the model file
  • n number of simulations.

A model file is just a data.frame with rows that represent inputs and outputs of the model. The columns include ID, label, whether the event is input or output, a distribution (for inputs), and a formula (for outputs).

The model file then can created in using the shiny interface, R or other software editors. The idea behind model files is that can be easy to share and modify.

# Load a model file from the package
M <- quantrra::OIRSA_M
# Run the model 5000 times
Mo <- ra_run(m = M, nsim = 5000)
# Visualize the results:
ra_plot_dist(Mo$P)

Other features

quantrra also provides functions to evaluate the model and creating stratified models to estimate regional or strata-specific risk estimation of events. see the package example for more information.

quantrra's People

Contributors

spablotemporal avatar

Stargazers

Thomas Rosendal avatar Alejandro Zaldivar Gómez avatar Natalia Ciria Artiga avatar Boris V. Schmid avatar

Watchers

 avatar

Forkers

trosendal

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