Different log-likelihood function

[hannahbav]

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)