c35829c9a7624fe9722543fb874d0aa2a7b8fb61,pyglmnet/pyglmnet.py,,_logL,#,127

Before Change

        logL = np.sum(nu * (-y / y_hat - np.log(y_hat)))
    elif distr == "neg-binomial":
        r = 15.
        C = np.sum(loggamma(y + r) - loggamma(y + 1) -
                   loggamma(r) + r * np.log(r))
        logL = C - np.sum(np.log(y_hat + r) * (y_hat + r) + y * np.log(y_hat))
    return logL

After Change

        logL = np.sum(nu * (-y / y_hat - np.log(y_hat)))
    elif distr == "neg-binomial":
        r = 15.
        logL =  np.sum(loggamma(y + r) + r * np.log(r) + y * np.log(y_hat) - loggamma(y + 1) -
                   loggamma(r) - np.log(y_hat + r) * (y + r))
    return logL

Instances