pastas.stats.metrics.sse#

pastas.stats.metrics.sse(obs: pandas.Series | None = None, sim: pandas.Series | None = None, res: pandas.Series | None = None, missing: str = 'drop', **kwargs) → float#

Compute the Sum of the Squared Errors (SSE).

Parameters:

  • obs (pandas.Series, optional) – The Series with the observed values.

  • sim (pandas.Series, optional) – Series with the simulated values.

  • res (pandas.Series, optional) – The Series with the residual values. If time series for the residuals are provided, the sim and obs arguments are ignored. Note that the residuals must be computed as obs - sim here.

  • missing (str, optional) – string with the rule to deal with missing values. Only “drop” is supported now.

Notes

The Sum of the Squared Errors (SSE) is calculated as follows:

\[\begin{split}\\text{SSE} = \\sum(\\epsilon^2)\end{split}\]

where \(\\epsilon\) are the errors.