Add cluster based estimator (#275)

### Proposed changes

Addresses #258 and #172.

Add new cluster based estimator. 

- Splits the space in a grid and determines the accumulated weight in
each cell.
- Starting from the weight peaks, it groups cells into clusters of ever
decreasing weight. It creates as many clusters as needed to cover all
the particle occupied space.
- Estimates mean and covariance for each.
- Returns the mean and covariance of the cluster with the highest
cumulative weight.

#### Type of change

- [ ] 🐛 Bugfix (change which fixes an issue)
- [x] 🚀 Feature (change which adds functionality)
- [ ] 📚 Documentation (change which fixes or extends documentation)

### Checklist

- [x] Lint and unit tests (if any) pass locally with my changes
- [x] I have added tests that prove my fix is effective or that my
feature works
- [x] I have added necessary documentation (if appropriate)
- [x] All commits have been signed for
[DCO](https://developercertificate.org/)

---------

Signed-off-by: Nahuel Espinosa <[email protected]>
Co-authored-by: Nahuel Espinosa <[email protected]>

beluga/include/beluga/algorithm.hpp

@@ -20,6 +20,7 @@
  * \brief Includes all beluga algorithms.
  */
 
+#include <beluga/algorithm/cluster_based_estimation.hpp>
 #include <beluga/algorithm/distance_map.hpp>
 #include <beluga/algorithm/effective_sample_size.hpp>
 #include <beluga/algorithm/estimation.hpp>