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IPF allows one to find a matrix S, close to an input matrix T, but such that the row sums of S are R, and the column sums of S are C.
Its useful in a range of tasks (I use it in traffic matrix problems), but is often used in statistics for examining independence assumptions in contingency tables.
See
http://en.wikipedia.org/wiki/Iterative_proportional_fitting
for more info (the verion implemented above is the RAS version from that page).
I have a more advanced version designed tofund S satisfying an arbitrary set of linear constraints, but its not quite in hand-out-able form, so ask me if you need it.
See internal documentation and ipf_test.m for details of how to use it.
Citation pour cette source
Matthew Roughan (2026). IPF (https://fr.mathworks.com/matlabcentral/fileexchange/24829-ipf), MATLAB Central File Exchange. Extrait(e) le .
Catégories
En savoir plus sur Quadratic Programming and Cone Programming dans Help Center et MATLAB Answers
Informations générales
- Version 1.0.0.0 (2,81 ko)
Compatibilité avec les versions de MATLAB
- Compatible avec toutes les versions
Plateformes compatibles
- Windows
- macOS
- Linux
| Version | Publié le | Notes de version | Action |
|---|---|---|---|
| 1.0.0.0 |
