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GaussianLikelihood#

class GaussianLikelihood[source]#

Gaussian likelihood function.

Notes

The Gaussian log-likelihood function is defined as:

\[\log(L) = -\frac{N}{2}\log(2\pi\sigma^2) + \frac{\sum_{i=1}^N - \epsilon_i^2}{2\sigma^2}\]

where \(N\) is the number of observations, \(\sigma^2\) is the variance of the residuals, and \(\epsilon_i\) is the residual at time \(i\). The parameter \(\sigma^2\) need to be estimated.

Methods#

__init__

compute

Compute the log-likelihood.

get_init_parameters

Get the initial parameters for the log-likelihood function.