_images/prest-logo.png


Introduction

Prest is a free and open-source desktop application for choice-based preference estimation.


Downloads

  • No installation required: run by double-clicking the .exe file.
    If Windows blocks Prest, right-click on the file and in “Properties -> General” select “Unblock”.
  • No installation required: run by double-clicking the .command file. Select “Open anyway” if prompted.
    If the “Open anyway” button is not available, close the dialog window and double-click the .command file again.
  • You can also follow these instructions to build Prest from source code & run it on any distro.
  • The Prest source code, written in Rust (core program) and Python (graphical user interface).

Previous downloadable versions are available in the archive.


Recently Added Features

  • Since v2.0.0: new suite of tests for datasets where the same menu is presented more than once.
    (support for possibly random choice data)
  • Since v2.0.0: new measure of model proximity for datasets with multiple choices per menu.
    (support for possibly multi-valued choice functions/correspondences)
  • Since v1.1.0: visualization of preference-estimation output using GraphViz .
    (the GraphViz binary file must be placed in the same directory as Prest)

Documentation

The pages linked below (also in the navigation menu on the left) contain information about Prest’s features, define the terms used in its graphical user interface, and explain relevant background concepts.

Tip

Text boxes with the Tip label provide essential information about Prest’s features.

Note

Text boxes with the Note label provide supplementary information.


Citation

Georgios Gerasimou and Matúš Tejiščák (2018) “Prest: Open-Source Software for Computational Revealed Preference Analysis”, Journal of Open Source Software, 3(30), 1015, doi:10.21105.joss.01015.


Declarations

  • Prest is open-source software and its latest version will always be available online for free.
  • Prest does not collect any data entered by its users.