True epidemic growth construction through harmonic analysis

Steven G. Krantz; Peter Polyakov; Arni S.R.Srinivasa Rao

doi:10.1016/j.jtbi.2020.110243

True epidemic growth construction through harmonic analysis

Steven G. Krantz, Peter Polyakov, Arni S.R.Srinivasa Rao

Research output: Contribution to journal › Article › peer-review

16 Scopus citations

Abstract

In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second phase, we used this partial data to generate plausible complete data through wavelets. We have provided two numerical examples. This procedure is novel and implementable and adaptable to machine learning modeling framework.

Original language	English (US)
Article number	110243
Journal	Journal of Theoretical Biology
Volume	494
DOIs	https://doi.org/10.1016/j.jtbi.2020.110243
State	Published - Jun 7 2020

Keywords

Convergence of graphs
Partial to complete data
Wavelets

ASJC Scopus subject areas

Statistics and Probability
Modeling and Simulation
General Biochemistry, Genetics and Molecular Biology
General Immunology and Microbiology
General Agricultural and Biological Sciences
Applied Mathematics

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10.1016/j.jtbi.2020.110243

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abstract = "In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second phase, we used this partial data to generate plausible complete data through wavelets. We have provided two numerical examples. This procedure is novel and implementable and adaptable to machine learning modeling framework.",

keywords = "Convergence of graphs, Partial to complete data, Wavelets",

author = "Krantz, {Steven G.} and Peter Polyakov and Rao, {Arni S.R.Srinivasa}",

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AU - Polyakov, Peter

AU - Rao, Arni S.R.Srinivasa

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AB - In this paper, we have proposed a two-phase procedure (combining discrete graphs and wavelets) for constructing true epidemic growth. In the first phase, a graph-theory-based approach was developed to update partial data available and in the second phase, we used this partial data to generate plausible complete data through wavelets. We have provided two numerical examples. This procedure is novel and implementable and adaptable to machine learning modeling framework.

KW - Convergence of graphs

KW - Partial to complete data

KW - Wavelets

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True epidemic growth construction through harmonic analysis

Abstract

Keywords

ASJC Scopus subject areas

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