pypomp.panel.panel.PanelPomp.arma

PanelPomp.arma(order: tuple[int, int, int] = (1, 0, 1), log_ys: bool = False, suppress_warnings: bool = True) → DataFrame

Fits an independent ARIMA model to the observation data for each unit and returns a DataFrame with the estimated log-likelihoods for each unit and the total.

This is a wrapper around pypomp.benchmarks.arma.

Parameters:

  • order (tuple, optional) – The (p, d, q) order for the ARIMA model. Defaults to (1, 0, 1).

  • log_ys (bool, optional) – If True, fits the model to log(y+1). Defaults to False.

  • suppress_warnings (bool, optional) – If True, suppresses individual warnings from statsmodels and issues a summary warning instead. Defaults to True.

Returns:

A DataFrame with columns ‘unit’ and ‘logLik’ containing results for each unit

and their sum (labeled as ‘[[TOTAL]]’ in the first row).

Return type:

pd.DataFrame