pypomp.panel.panel.PanelPomp.mif

PanelPomp.mif(J: int, M: int, rw_sd: RWSigma, key: Array | None = None, theta: PanelParameters | None = None, thresh: float = 0.0, n_monitors: int = 0, block: bool = True) → None

Estimate parameters using the Panel Iterated Filtering (PIF) algorithm for PanelPomp.

Parameters:

  • J (int) – Number of particles per unit.

  • M (int) – Number of iterations (cooling cycles).

  • rw_sd (RWSigma) – Random walk standard deviations for parameter perturbations.

  • key (jax.Array, optional) – JAX random key. If None, uses self.fresh_key.

  • theta (PanelParameters, optional) – Initial parameter estimates. If None, uses self.theta.

  • thresh (float) – Resampling threshold for the particle filter.

  • n_monitors (int) – Number of particle filter runs to average for log-likelihood estimation. Defaults to 0 (uses estimate from perturbed filter).

  • block (bool) – Whether to use block updates, i.e., Marginalized Panel Iterated Filtering (MPIF). Uses Panel Iterated Filtering (PIF) if False.

Returns:

None. Updates self.theta with final estimates and adds a PanelPompMIFResult to self.results_history.