Statistics and Extreme Value Analysis#

Statistics and performance metrics#

`skills.bias`(sim, obs[, dim])	Return the bias between two time series.
`skills.percentual_bias`(sim, obs[, dim])	Return the percentual bias between two time series.
`skills.volumetric_error`(sim, obs[, dim])	Return the volumetric error between two time series.
`skills.nashsutcliffe`(sim, obs[, dim])	Return the Nash-Sutcliffe model efficiency.
`skills.lognashsutcliffe`(sim, obs[, epsilon, dim])	Return the log Nash-Sutcliffe model efficiency.
`skills.pearson_correlation`(sim, obs[, dim])	Return the Pearson correlation coefficient of two time series.
`skills.spearman_rank_correlation`(sim, obs[, dim])	Return the spearman rank correlation coefficient of two time series.
`skills.kge`(sim, obs[, dim])	Return the Kling-Gupta Efficiency (KGE) of two time series.
`skills.kge_2012`(sim, obs[, dim])	Return the Kling-Gupta Efficiency (KGE, 2012) of two time series.
`skills.kge_non_parametric`(sim, obs[, dim])	Return the Non Parametric Kling-Gupta Efficiency (KGE, 2018).
`skills.kge_non_parametric_flood`(sim, obs[, dim])	Return the Non Parametric Kling-Gupta Efficiency (KGE, 2018) of two time series.
`skills.rsquared`(sim, obs[, dim])	Return the coefficient of determination of two time series.
`skills.mse`(sim, obs[, dim])	Return the mean squared error (MSE) between two time series.
`skills.rmse`(sim, obs[, dim])	Return the root mean squared error between two time series.
`skills.rsr`(sim, obs[, dim])	Return the RMSE-observations standard deviation (RSR) between two time series.

`extremes.get_peaks`(da[, ev_type, min_dist, ...])	Return peaks from time series.
`extremes.fit_extremes`(da_peaks[, ...])	Return distribution fit from extremes.
`extremes.get_return_value`(da_params[, rps, ...])	Return return value based on EVA.
`extremes.eva`(da[, ev_type, min_dist, ...])	Return Extreme Value Analysis.

Return peak hydrographs.