The poems package provides a framework of interoperable R6 (Chang, 2020) classes for building ensembles of viable models via the pattern-oriented modeling (POM) approach (Grimm et al., 2005). The package includes classes for encapsulating and generating model parameters, and managing the POM workflow. The workflow includes:
- Model setup including generated spatial layers and demographic population model parameters.
- Generating model parameters via Latin hypercube sampling (Iman & Conover, 1980).
- Running multiple sampled model simulations.
- Collating summary results metrics via user-defined functions.
- Validating and selecting an ensemble of models that best match known patterns.
By default, model validation and selection utilizes an approximate Bayesian computation (ABC) approach (Beaumont et al., 2002) using the abc package (Csillery et al., 2015). However, alternative user-defined functionality could be employed.
The package includes a spatially explicit demographic population model simulation engine, which incorporates default functionality for density dependence, correlated environmental stochasticity, stage-based transitions, and distance-based dispersal. The user may customize the simulator by defining functionality for trans-locations, harvesting, mortality, and other processes, as well as defining the sequence order for the simulator processes. The framework could also be adapted for use with other model simulators by utilizing its extendable (inheritable) base classes.
Beaumont, M. A., Zhang, W., & Balding, D. J. (2002). ‘Approximate Bayesian computation in population genetics’. Genetics, vol. 162, no. 4, pp, 2025–2035. doi:10.1093/genetics/162.4.2025
Chang, W. (2020). ‘R6: Encapsulated Classes with Reference Semantics’. R package version 2.5.0. Retrieved from https://CRAN.R-project.org/package=R6
Csillery, K., Lemaire L., Francois O., & Blum M. (2015). ‘abc: Tools for Approximate Bayesian Computation (ABC)’. R package version 2.1. Retrieved from https://CRAN.R-project.org/package=abc
Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., Thulke, H. H., Weiner, J., Wiegand, T., DeAngelis, D. L., (2005). ‘Pattern-Oriented Modeling of Agent-Based Complex Systems: Lessons from Ecology’. Science vol. 310, no. 5750, pp. 987–991. doi:10.1126/science.1116681