Title: Pattern-Oriented Ensemble Modeling System
person("Sean", "Haythorne", email = "sean.haythorne@adelaide.edu.au", role = c("aut", "cre")),
person("Damien", "Fordham", email = "damien.fordham@adelaide.edu.au", role = "aut"),
person("Stuart", "Brown", email = "s.brown@adelaide.edu.au", role = "aut"),
person("Jessie", "Buettel", email = "jessie.buettel@utas.edu.au", role = "aut"),
person("Barry", "Brook", email = "barry.brook@utas.edu.au", role = "aut"))
Description: The poems package provides a framework of interoperable R6 classes for
building ensembles of viable models via the pattern-oriented modeling (POM)
approach. The package includes classes for encapsulating and generating model
parameters, and managing the POM workflow. The workflow includes: model setup;
generating model parameters via Latin hyper-cube sampling; running multiple sampled
model simulations; collating summary results; and 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, although
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 translocations, 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.
Collate: 'GenericClass.R' 'Region.R' 'GenericModel.R' 'SpatialModel.R'

Description: The poems package provides a framework of interoperable R6 classes
(Chang, 2020, <https://CRAN.R-project.org/package=R6>) for building ensembles
of viable models via the pattern-oriented modeling (POM) approach (Grimm et al.,
2005, <doi:10.1126/science.1116681>). The package includes classes for
encapsulating and generating model parameters, and managing the POM workflow.
The workflow includes: model setup; generating model parameters via Latin
running multiple sampled model simulations; collating summary results; and
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,
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 translocations, harvesting,
simulator processes. The framework could also be adapted for use with other
model simulators by utilizing its extendable (inheritable) base classes.