stockflow: Create a new stock-and-flow model

Description

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)

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.

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)

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.

Examples

Run this code

sfm <- stockflow()
summary(sfm)

# \dontshow{
sfm <- sim_settings(sfm, save_at = 1)
# }

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