| 1 | <h1>Clustering into regions of synchronous variations</h1> |
| 2 | |
| 3 | <p>Joint work with <a href="http://www.cmap.polytechnique.fr/~giraud/">Christophe Giraud</a>.</p> |
| 4 | |
| 5 | <hr/> |
| 6 | |
| 7 | <p>This R package implements a clustering method described in detail in <a href="http://www.cmap.polytechnique.fr/~giraud/SynchronousPop.pdf">this article</a>.</p> |
| 8 | |
| 9 | <p>The goal is to divide a map of observational sites into regions of similar intra-variability over the years, but |
| 10 | with distinct dynamics compared to other regions. |
| 11 | The problem has both spatial (the sites) and temporal (measurements every year) aspects, and is difficult because |
| 12 | there are no a priori indications about the regions.</p> |
| 13 | |
| 14 | <hr/> |
| 15 | |
| 16 | <p>Two (heuristic) methods are available in the package, either direct graph clustering or parameters estimation |
| 17 | in a model-based formulation of the problem.</p> |
| 18 | |
| 19 | <p> |
| 20 | Main function to cluster populations data: <code>findSyncVarRegions()</code>.</p> |