actuarialopensource / actuarialopensource/benchmarks

Big-O notation, find a resolution

Ouverte
#50 2 commentaires 0 réactions 0 personnes assignées Voir sur GitHub
Langage dominant
Python
Étoiles
16
Forks
4
Métriques de merge des PR
Aucune PR mergée en 30 j

Description

We have an approach for Big-O notation memory complexity in the case of our iterative Julia models - #34. I wanted a way of doing this for lifelib models and had an idea I thought would work, but it doesn't seem like we should do it - #49.

We want to classify or categorize different common approaches to actuarial modeling by this Big-O notation.

* Seriatim memoized
* Vectorized memoized
* Iterative

It is possible that we simplify the model while maintaining the same fundamental structure and then sort of just make an appeal to logic/math in the way that a computer scientist might. Then the argument for big-O notation isn't dependent on a specific implementation?

Anyhow, we don't have argument that the lifelib models *should* satisfy certain properties. Like Seriatim having different memory complexity than vectorized is sort of obvious in some sense, but saying it in the right way might be necessary to really have done the topic justice in my opinion.

Guide de contribution

Ouvrir le guide de contribution

Évaluation

Cette issue n'a pas encore été évaluée.

Recevez les nouvelles issues par e-mail

Un résumé court des issues GitHub adaptées aux débutants.