Multivariate Regularized Newton and Levenberg-Marquardt methods: a comparison on synthetic data of tumor hypoxia in a kinetic framework
In this paper we propose a new algorithm to optimize the parameters of a compartmental problem describing tumor hypoxia. The method is based on a multivariate Newton approach, with Tikhonov regularization, and can be easily applied to data with diverse statistical distributions. Here we simulate [18...
Main Authors: | Garbarino Sara, Caviglia Giacomo |
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Format: | Article |
Language: | English |
Published: |
Sciendo
2019-01-01
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Series: | Communications in Applied and Industrial Mathematics |
Subjects: | |
Online Access: | https://doi.org/10.2478/caim-2019-0006 |
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