A new algorithm for computing the multivariate Fa\`a di Bruno's formula
E. Di Nardo, G. Guarino, D. Senato
TL;DR
This paper introduces a symbolic algorithm based on umbral calculus for efficiently computing the multivariate Faà di Bruno's formula, significantly improving computational speed over existing methods.
Contribution
It presents a novel MAPLE procedure utilizing umbral calculus to compute the multivariate Faà di Bruno's formula more efficiently.
Findings
Faster computational times compared to existing algorithms
Successful implementation of a MAPLE procedure
Applications demonstrating the method's effectiveness
Abstract
A new algorithm for computing the multivariate Fa\`a di Bruno's formula is provided. We use a symbolic approach based on the classical umbral calculus that turns the computation of the multivariate Fa\`a di Bruno's formula into a suitable multinomial expansion. We propose a MAPLE procedure whose computational times are faster compared with the ones existing in the literature. Some illustrative applications are also provided.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsProbability and Statistical Research · Data Management and Algorithms · Advanced Database Systems and Queries