Spatiotemporal Point Patterns Simulation
Proportional (probability) distribution
Geometry and Coordinate Reference System test of a polygon
Stpp from synthetic origins
Stpp from real (sample) origins
Snapping point to network
Make square grids
Artificial spatial origins
Boundary surrounding a set of points
Compare two areas
Date (Format) Checker
Coordinates extraction
Global temporal pattern (GTP)
Near Repeat calculator using the Knox test
Space restriction raster map
Spatial and temporal model
Learning the spatiotemporal properties of a sample data
A landscape walker
Generates artificial point patterns marked by their spatial and temporal signatures. The resulting point cloud may exhibit inherent interactions between both signatures. The simulation integrates microsimulation (Holm, E., (2017)<doi:10.1002/9781118786352.wbieg0320>) and agent-based models (Bonabeau, E., (2002)<doi:10.1073/pnas.082080899>), beginning with the configuration of movement characteristics for the specified agents (referred to as 'walkers') and their interactions within the simulation environment. These interactions (Quaglietta, L. and Porto, M., (2019)<doi:10.1186/s40462-019-0154-8>) result in specific spatiotemporal patterns that can be visualized, analyzed, and used for various analytical purposes. Given the growing scarcity of detailed spatiotemporal data across many domains, this package provides an alternative data source for applications in social and life sciences.
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