**Seventh
Sense Software** actively takes part in multivariate
statistical research. The company has developed several state-of-the-art
statistical algorithms and has made a number of important mathematical discoveries
in pure statistics. Amongst them are the following:

Derivation of a **rigorous
entropic approach to the general multivariate density estimation problem**,
namely that of finding the population probability distribution which best
fits a given set of multivariate data samples.

Development of the **world's
fastest single-link clustering algorithm** for Euclidean data sets.
The algorithm is both storage efficient, coping easily with enormous data
sets, and parallelisable for time-critical applications.

Development of **advanced
multiresolution edge detection techniques** for removal of mixed
pixels from multispectral imagery to enhance results from density-based
hierarchical clustering techniques such as the single-link method.

Discovery of an important one-to-one
relationship between the minimal spanning tree resulting from single-link
clustering of a data set and its sample density distribution, leading to
the development of the so-called **"bubble model"
density estimator.**

Development of **improved
parameter estimators and hypothesis testing methods** for spatial
Poisson processes.

Development of a **fast,
self-consistent and iterative approach**
to locally-adaptive multivariate kernel density estimation which
allows rapid convergence to a final solution even with high-dimensional
data.