pypomp.models.dhaka¶
- pypomp.models.dhaka(dt: float | None = 0.004166666666666667, nstep: int | None = None, gamma: bool = False) Pomp[source]¶
Creates a POMP model for the Dhaka cholera data.
This function constructs a Partially Observed Markov Process (POMP) model for the Dhaka cholera dataset. The model includes a stochastic process for the underlying disease dynamics and a measurement model for observed deaths.
- Parameters:
dt (float, optional) – Time step size for the process model. Determines the number of sub-steps per observation interval for the process model.
nstep (int, optional) – Number of sub-steps per observation interval for the process model. If None, uses Euler discretization with the specified step size. nstep and dt cannot both be not None.
gamma (bool, optional) – Indicator for whether gamma white noise should be used in place of Gaussian noise. This corresponds to a large-population approximation of an overdispersed death process.
Model Parameters
- gammafloat
Recovery rate (duration of infectiousness).
- epsilonfloat
Rate of waning of immunity for severe infections.
- rhofloat
Rate of waning of immunity for inapparent infections.
- mfloat
Cholera-specific mortality rate.
- cfloat
Fraction of infections that lead to severe (clinically apparent) infection.
- beta_trendfloat
Slope of the secular trend in transmission.
- bs1-bs6float
Seasonal transmission rates (B-spline coefficients).
- sigmafloat
Environmental noise intensity.
- taufloat
Measurement error standard deviation.
- alphafloat
Non-linear transmission parameter.
- deltafloat
Natural mortality rate.
- S_0, I_0, Y_0, R1_0, R2_0, R3_0float
Initial value parameters (IVPs) for the model state proportions.
- omegas1-omegas6float
Seasonal environmental reservoir parameters (B-spline coefficients for the log-reservoir).
- Returns:
A POMP model object representing the Dhaka cholera model.
- Return type: