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.

Extreme Value Analysis

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.

Design Events

design_events.get_peak_hydrographs(da, ...)

Return peak hydrographs.