Ctrl K

quafing

Questionnaire analysis using Fisher Information Non-Parametric Embedding. Explore high-dimensional continuous and discrete questionnaire data sets.

3
contributors
132 commitsLast commit ≈ 30 months ago1 star0 forks

Cite this software

DOI:

10.5281/zenodo.7847644

Description

Questionnaire analysis using Fisher Information Non-Parametric Embedding enables users to explore the similarity of respondent groups by leveraging the information distance between the multi-dimensional probability density functions of each group - i.e. the most appropriate distance metric - to provide input for lower dimensional embedding and visualization.
Quafing supports (mixed) continuous and discrete data responses.
WIP

Keywords
Data Analysis
python
Statistics
Programming languages
License
</>Source code

Participating organisations

Netherlands eScience Center
University of Amsterdam

Contributors

Contact person

Meiert Willem Grootes
Meiert Willem Grootes
Meiert Willem Grootes
Lead RSE
Netherlands eScience Center
Pranav Chandramouli
Pranav Chandramouli
eScience Research Engineer
Netherlands eScience Center
DR

Related projects

Computing societal dynamics of climate change adaptation in cities

Decision-support tools for the societal dynamics of climate change adaptation

Updated 1 month ago
Finished