pastas.stats.metrics#

The following methods may be used to describe the fit between the model simulation and the observations.

Examples

These methods may be used as follows:

>>> ps.stats.rmse(sim, obs)

or

>>> ml.stats.rmse()

Functions

aic

Compute the Akaike Information Criterium (AIC).

bic

Compute the Bayesian Information Criterium (BIC).

evp

Compute the (weighted) Explained Variance Percentage (EVP).

kge_2012

Compute the (weighted) Kling-Gupta Efficiency (KGE).

mae

Compute the (weighted) Mean Absolute Error (MAE).

nse

Compute the (weighted) Nash-Sutcliffe Efficiency (NSE).

pearsonr

Compute the (weighted) Pearson correlation (r).

rmse

Compute the (weighted) Root Mean Squared Error (RMSE).

rsq

Compute R-squared, possibly adjusted for the number of free parameters.

sse

Compute the Sum of the Squared Errors (SSE).