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Dynamic Max Coun
This contains the ideas and notes for a Dynamic Max Count (Dynamic Max-in-time) aggregate operator
Concept
Instead of using Hyper-buckets that have discrete boundaries and densities which can not be updated reasonably using the MaxCountProgramNotes ideas, we propose a probabilistic method where by we put probability densities in space. Each probability density will need the following properties:
- Parameters that define the distribution e.g.
- Center location
- Spatial size
- Standard deviation
- A measure of symmetry or skew
A multi-dimensional probability function preferably a function that uses types functions as parameters e.g. latex2(
)A theory to update, delete or insert points and the distributions based on changes to points.
Based on this last item, we must maintain a database of 4-dimensional points that we index using 4-dimensional, probability buckets.