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

Sara Hamis; Stanislav Stratiev; Gibin G. Powathil

doi:10.1142/9789811223495_0001

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 proceeding › Chapter

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 language	English
Title of host publication	The Physics of Cancer
Subtitle of host publication	Research Advances
Editors	Bernard S Gerstman
Publisher	World Scientific Publishing Co. Pte Ltd
Pages	1-37
Number of pages	37
Volume	Singapore
ISBN (Electronic)	9789811223501
ISBN (Print)	9789811223488
DOIs	https://doi.org/10.1142/9789811223495_0001
Publication status	Published - 16 Dec 2020

Keywords

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

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1142/9789811223495_0001

Cite this

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title = "Uncertainty and sensitivity analyses methods for agent-based mathematical models: an introductory review",

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.",

keywords = "Sensitivity analysis, Agent-based models, Cancer model, Consistency analysis, Robustness analysis, Latin hypercube analysis",

author = "Sara Hamis and Stanislav Stratiev and Powathil, {Gibin G.}",

note = "Funding: SH was supported by the Medical Research Council [grant code MR/R017506/1] and Swansea University PhD Research Studentship. SS was supported by an STFC studentship under the DTP grant ST/N504464/1.",

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doi = "10.1142/9789811223495_0001",

language = "English",

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booktitle = "The Physics of Cancer",

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Uncertainty and sensitivity analyses methods for agent-based mathematical models: an introductory review. / Hamis, Sara; Stratiev, Stanislav; Powathil, Gibin G.
The Physics of Cancer: Research Advances. ed. / Bernard S Gerstman. Vol. Singapore World Scientific Publishing Co. Pte Ltd, 2020. p. 1-37.

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - Uncertainty and sensitivity analyses methods for agent-based mathematical models

T2 - an introductory review

AU - Hamis, Sara

AU - Stratiev, Stanislav

AU - Powathil, Gibin G.

N1 - Funding: SH was supported by the Medical Research Council [grant code MR/R017506/1] and Swansea University PhD Research Studentship. SS was supported by an STFC studentship under the DTP grant ST/N504464/1.

PY - 2020/12/16

Y1 - 2020/12/16

N2 - 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.

AB - 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.

KW - Sensitivity analysis

KW - Agent-based models

KW - Cancer model

KW - Consistency analysis

KW - Robustness analysis

KW - Latin hypercube analysis

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DO - 10.1142/9789811223495_0001

M3 - Chapter

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BT - The Physics of Cancer

A2 - Gerstman, Bernard S

PB - World Scientific Publishing Co. Pte Ltd

ER -

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

Abstract

Keywords

UN SDGs

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