[mle] Replace np.sum with @, fix typos, and use gammaln for stable Poisson log-likelihood #473
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…ve numerical stability using scipy.special.gammaln
oyamad
reviewed
Jun 25, 2025
lectures/mle.md
Outdated
| @@ -458,7 +458,7 @@ class PoissonRegression: | |||
| def logL(self): | |||
| y = self.y | |||
| μ = self.μ() | |||
| return np.sum(y * np.log(μ) - μ - np.log(factorial(y))) | |||
| return np.sum(y * np.log(μ) - μ - scipy.special.gammaln(y + 1)) | |||
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- Add
gammalntofrom scipy.special import factorial. - I second this change, but an explanation should be given in the text, why
gammaln(y + 1)is preferred tonp.log(factorial(y)).
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Replace np.sum(a * b) with a @ b
#463
Fix typos in Tex
Replaced np.log(factorial(y)) with scipy.special.gammaln(y + 1) for improved numerical stability and accuracy, especially for large values of y.