unbinned_maximum_likelihood

minkit.unbinned_maximum_likelihood(pdf, data, range='full')[source]

Definition of the unbinned maximum likelihood FCN. The given PDF must not be of extended type. The output is two times the logarithm of the likelihood, and is computed as

\[\text{FCN} = -2 \times \left[\sum_{i=0}^N \log \frac{f(\vec{x}_i;\vec{\theta})}{A(\vec{\theta})}\right],\]

where \(f(\vec{x}_i;\vec{\theta})\) is the function to minimize (without normalization), \(\vec{x}_i\) are the data points, \(\vec{\theta}\) are the function parameters and \(A(\vec{\theta})\) is the normalization value.

Parameters
  • pdf (PDF) – function to evaluate.

  • data (DataSet) – data to evaluate.

  • range (str) – normalization range of the PDF.

Returns

value of the FCN.

Return type

float