Description Usage Arguments Value Note References Examples

Generate a spatPomp object for measles in the top-`U`

most populous cities in England and Wales.
The model is adapted from He et al. (2010) with gravity transport following Park and Ionides (2019).
The data in the object is simulated using the process and measurement models of He et al. (2010).

1 2 3 4 5 6 7 8 9 |

`U` |
A length-one numeric signifying the number of cities to be represented in the spatPomp object. |

`dt` |
a numeric (in unit of years) that is used as the Euler time-increment for simulating measles data. |

`fixed_ivps` |
a logical. If |

`shared_ivps` |
a logical. If |

`S_0` |
a numeric. If |

`E_0` |
a numeric. If |

`I_0` |
a numeric. If |

An object of class ‘spatPomp’ representing a `U`

-dimensional spatially coupled measles POMP model.

This function goes through a typical workflow of constructing
a typical spatPomp object (1-4 below). This allows the user to have a
file that replicates the exercise of model building as well as function
that creates a typical nonlinear model in epidemiology in case they want
to test a new inference methodology. We purposely do not modularize this
function because it is not an operational piece of the package and is
instead useful as an example.

1. Getting a measurements data.frame with columns for times,
spatial units and measurements.

2. Getting a covariates data.frame with columns for times,
spatial units and covariate data.

3. Constructing model components (latent state initializer,
latent state transition simulator and measurement model). Depending
on the methods used, the user may have to supply a vectorfield to
be integrated that represents the deterministic skeleton of the latent
process.

4. Bringing all the data and model components together to form a
spatPomp object via a call to spatPomp().

1 2 3 | ```
m <- measles(U = 5)
# See all the model specifications of the object
spy(m)
``` |

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