Maximum Likelihood Estimation

class pbparam.MLE

Maximum Likelihood Estimation (MLE) class, to evaluate error of simulation dataset to true dataset.

Parameters:

• y_sim (array or list) – contains simulation data points

• y_data (array or list) – contains reference data points

• weights (dict, optional) – weights of the parameters

• sd (float, optional) – standard deviation of error, not all cost function need it.

Returns:

MLE – Calculated MLE for given inputs.

Return type:

array

evaluate(y_sim, y_data, weights, sd)

Placeholder method for evaluating the cost of a prediction

Subclasses will override this method to provide specific implementations

Parameters:

• y_sim (array-like) – predicted values

• y_data (array-like) – actual values

• weights (dict, optional) – weights of the parameters

• sd (float, optional) – standard deviation of error, not all cost function need it.