The default behavior for adding and solving with noisemodels has changed from Pastas 1.5. Find more information here

pastas.stats.core#

The following methods may be used to calculate the crosscorrelation and autocorrelation for a time series.

These methods are ‘special’ in the sense that they are able to deal with irregular time steps often observed in hydrological time series.

Functions

acf

Calculate the autocorrelation function for irregular time steps.

ccf

Method to compute the cross-correlation for irregular time series.

mean

Method to compute the (weighted) mean of a time series.

std

Method to compute the (weighted) variance of a time series.

var

Method to compute the (weighted) variance of a time series.