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In the paper, the log likelihood is the sum of cancel rates times log probabilities, plus the end survived rate times final survivor likelihood. Should it therefore not be
def log_likelihood(alpha, beta, data, survivors=None):
if alpha <= 0 or beta <= 0:
return -1000
if survivors is None:
survivors = cancel_rates
probabilities = generate_probabilities(alpha, beta, len(data))
final_survivor_likelihood = survivor(probabilities, len(data) - 1)
return sum([s * np.log(probabilities[t]) for t, s in enumerate(data)]) + survivors[-1] * np.log(final_survivor_likelihood)
The text was updated successfully, but these errors were encountered:
In the paper, the log likelihood is the sum of cancel rates times log probabilities, plus the end survived rate times final survivor likelihood. Should it therefore not be
The text was updated successfully, but these errors were encountered: