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Create a new stock-and-flow model

Source: R/stockflow.R
stockflow.Rd

Initialize a stock-and-flow model of class stockflow. You can either create an empty stock-and-flow model or load a template from the model library.

Usage

stockflow(template = NULL)

Arguments

template

Name of the template to load. If NULL, an empty stock-and-flow model will be created with default simulation parameters and a default meta. If specified, template should be one of the available templates (case-insensitive):

  • logistic_model: Population growth with carrying capacity

  • sir: Epidemic model (Susceptible-Infected-Recovered)

  • predator_prey: Lotka-Volterra dynamics

  • cusp: Cusp catastrophe model

  • crielaard2022: Eating behavior (doi: 10.1037/met0000484)

  • coffee_cup: Temperature equilibration (Meadows)

  • bank_account: Compound interest (Meadows)

  • lorenz: Lorenz attractor (chaotic)

  • rossler: Rossler attractor (chaotic)

  • vanderpol: Van der Pol oscillator

  • duffing: Forced Duffing oscillator

  • chua: Chua's circuit (chaotic)

  • jdr: Job Demands-Resources Theory as formalized in Evers et al. (under review)

Value

A stock-and-flow model object of class stockflow. Its structure is based on XML Interchange Language for System Dynamics (XMILE). It is a nested list, containing:

meta

Meta-information about model. A list containing arguments listed in meta().

sim_settings

Simulation specifications. A list containing arguments listed in sim_settings().

model

Model variables, grouped under the variable types stock, flow, aux (auxiliaries), constant, gf (graphical functions), and func (custom functions). Each variable contains arguments as listed in update().

Use summary() to run model diagnostics, as.data.frame() to convert to a data.frame, plot() to visualize.

Details

Do not edit the object manually; this will likely lead to errors downstream. Rather, use meta(), sim_settings(), update(), and custom_func() for safe manipulation.

See also

update(), meta(), custom_func(), sim_settings()

Examples

sfm <- stockflow()
summary(sfm)
#> 
#> ── Stock-and-Flow Model Diagnostics ────────────────────────────────────────────
#> 
#> ── Problem (1) ──
#> 
#> ! Model has no stocks.
#> → Add at least one stock with `stock()` or `update()`.
#> 
#> ── Potential problem (1) ──
#> 
#> • Model has no flows.
#> → Add flows with `flow()` or `update()`.


# Load a template
sfm <- stockflow("lorenz")
sim <- simulate(sfm)
plot(sim)