pastas.noisemodels.ArNoiseModel#
- class pastas.noisemodels.ArNoiseModel(norm: bool = True)#
Noise model with exponential decay of the residuals and weighting.
- Parameters:
norm (boolean, optional) – Boolean to indicate whether weights are normalized according to the Von Asmuth and Bierkens (2005) paper. Default is True.
Notes
Calculates the noise von Asmuth and Bierkens [2005] according to:
\[v(t_1) = r(t_1) - r(t_0) * \exp(- \Delta t / \alpha)\]Calculates the weights as
\[w = 1 / \sqrt{(1 - \exp(-2 \Delta t / \alpha))}\]The units of the alpha parameter is always in days. The first value of the noise is the residual (\(v(t=0=r(t=0)\)). First weight is 1 / sig_residuals (i.e., delt = infty). Normalization of weights as in von Asmuth and Bierkens [2005], optional.
Methods#
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Simulate noise from the residuals. |
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Method to calculate the weights for the noise. |
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Get the correction for a forecast using the noise model. |
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Method to return a dict to store the noise model |