weighted_estimate.py

from numpy import ndarray
import numpy as np

class WeightedEstimate:
    def __init__(self, λs):
        self.λs = λs


    def update(self, model_probabilities: ndarray) -> float:
        """
        Calculate the most likely model and the weighted mass estimate.
        """
        # Determine the most likely model after updating probabilities
        most_likely_model_index = np.argmax(model_probabilities)
        most_likely_parameter = self.λs[most_likely_model_index]

        # Calculate the weighted parameter estimate
        weighted_mass_estimate = np.sum([p * λ for p, λ in zip(model_probabilities, self.λs)])

        return weighted_mass_estimate