Uncertainty and sensitivity analyses methods for agent-based mathematical models: an introductory review

Sara Hamis, Stanislav Stratiev, Gibin G. Powathil

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Citation (Scopus)

Abstract

Multiscale, agent-based mathematical models of biological systems are often associated with model uncertainty and sensitivity to parameter perturbations. Here, three uncertainty and sensitivity analyses methods, that are suitable to use when working with agent-based models, are discussed. These methods are namely Consistency Analysis, Robustness Analysis and Latin Hypercube Analysis. This introductory review discusses origins, conventions, implementation and result interpretation of the aforementioned methods. Information on how to implement the discussed methods in MATLAB is included.
Original languageEnglish
Title of host publicationThe Physics of Cancer
Subtitle of host publicationResearch Advances
EditorsBernard S Gerstman
PublisherWorld Scientific Publishing Co. Pte Ltd
Pages1-37
Number of pages37
VolumeSingapore
ISBN (Electronic)9789811223501
ISBN (Print)9789811223488
DOIs
Publication statusPublished - 16 Dec 2020

Keywords

  • Sensitivity analysis
  • Agent-based models
  • Cancer model
  • Consistency analysis
  • Robustness analysis
  • Latin hypercube analysis

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