Example generators — dust

Load example generators from dust2. These generators exist primarily for the examples and documentation and are not (yet) very interesting. The examples will likely change as the package evolves and some may be removed.

Usage

dust_example(name)

Arguments

name: The name of the generator as a string; one of sir, sirode or walk. See Details.

Value

A dust_generator object, which you might pass into dust_system_create

Details

All models exist as source code in the package; to view the sir model you could write:

file.show(system.file("examples/sir.cpp", package = "dust2"))

`sir`

A simple SIR (Susceptible-Infected-Recovered) compartmental model. This model has parameters:

N: total population size
I0: initial infected population size (when using dust_system_set_state_initial)
beta: per-contact rate of infection
gamma: rate of recovery
exp_noise: noise parameter used in the comparison to data

The system will have compartments S, I, R, cases_cumul and cases_inc

`sirode`

The same model as sir but in continuous time, deterministically

`walk`

A random walk in discrete time with Gaussian increments. This model has parameters:

sd: The standard deviation of the Gaussian update (per unit time)
len: The number of independent walks
random_initial`: Boolean, indicating if the initial position should be random (changes how dust_system_set_state_initial would initialise the system)

Examples

walk <- dust_example("walk")
walk
#> 
#> ── <dust_system_generator: walk> ───────────────────────────────────────────────
#> ℹ Use 'dust2::dust_system_create()' to create a system with this generator
#> ℹ This system runs in discrete time with a default dt of 1
#> ℹ This system has 3 parameters
#> → 'sd', 'len', and 'random_initial'
#> ℹ Use 'coef()' to get more information on parameters

sys <- dust_system_create(walk, list(sd = 1), 20)
y <- dust_system_simulate(sys, 0:50)
matplot(t(y[1, , ]), type = "l", col = "#0000ff55", lty = 1,
        xlab = "Time", ylab = "Value")