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News

v 1.0.1.9000

This is the current development version.

v1.0.1

  • Minor bug fixes

v1.0.0

Overview

This is the first version of patter. The main thrust of the package is the provision of particle algorithms for the reconstruction of animal movement paths and emergent patterns of space, with a focus on passive acoustic telemetry systems. The package evolved from the predecessor flapper package, but is simpler, faster, more powerful, better tested and easier to maintain. While current functionality remains more streamlined than flapper, internal routines---which now used a specialised, fast Julia backend (Patter.jl)---alongside the API and supporting documentation are substantially improved. The package also benefits from fewer dependencies and has been fully upgraded in line with the evolution of R's spatial packages (with terra and sf superseding raster, sp, rgeos and associates). Please provide feedback on the new package. Much work remains!

De-novo simulation

The sim_*() functions in flapper have been replaced with faster and more flexible alternatives, including:

  • sim_path_walk(), which replaces flapper::sim_path_sa();
  • sim_array(), which replaces flapper::sim_array();
  • sim_observations(), which replaces flapper::sim_detections();

Particle filter

The pf_filter() function implements the particle filter. This brings together and enhances the ac(), dc(), acdc() and pf() functions in flapper. A major benefit of this integration is that the likelihood of simulated locations is evaluated exclusively at particle locations, rather than across the entire grid (as in ac(), dc() and acdc()), which is much faster. pf_filter() also reparameterises the forward simulation of individual locations with a stochastic kick methodology. In flapper, we simulated new locations by calculating movement probabilities into surrounding grid cells and then sampling grid cells in line with those probabilities (a directed sampling methodology). This approach has some significant benefits but becomes prohibitively expensive as grid size (area and resolution) increases. In patter, the stochastic-kick methodology simulates new locations by 'kicking' previous locations using a movement model. Stochastic kicks are independent of grid resolution, so this approach is much faster.

Backward smoother

The pf_smoother_two_filter() implements particle smoothing. This is a major new routine that substantially refines maps of space use.

Mapping

For mapping, map_pou() replaces flapper::pf_plot_map() and resolves an issue with the calculation of weights. map_dens() is a new function for the reconstruction of maps is based on spatstat routines. This function accounts for particle weights and fits smooth utilisation distributions using cross validation, superseding approaches in flapper based on adehabitatHR. Both approaches can be flexibly implemented using a data.table of coordinates and are not restricted to particle samples. The map_hr_*() routines for the reconstruction of home ranges are re-implementations of the get_hr_*() functions in flapper.

For the comparison of simulated and reconstructed patterns, the new skill_*() functions can be used.