Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission
(1) Background: The stochastic nature of agent-based models (ABMs) may be responsible for the variability of simulated outputs. Multiple simulation runs (i.e., replicates) need to be performed to have enough sample size for hypothesis testing and validating simulations. The simulation outputs in the...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-09-01
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| Series: | ISPRS International Journal of Geo-Information |
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| Online Access: | https://www.mdpi.com/2220-9964/10/9/604 |
| _version_ | 1797518973053435904 |
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| author | Jeon-Young Kang Jared Aldstadt |
| author_facet | Jeon-Young Kang Jared Aldstadt |
| author_sort | Jeon-Young Kang |
| collection | DOAJ |
| description | (1) Background: The stochastic nature of agent-based models (ABMs) may be responsible for the variability of simulated outputs. Multiple simulation runs (i.e., replicates) need to be performed to have enough sample size for hypothesis testing and validating simulations. The simulation outputs in the early-stage of simulations from non-terminating ABMs may be underestimated (or overestimated). To avoid this initialization bias, the simulations need to be run for a burn-in period. This study proposes to use multiple scale space-time patterns to determine the number of required replicates and burn-in periods in spatially explicit ABMs, and develop an indicator for these purposes. (2) Methods: ABMs of vector-borne disease transmission were used as the case study. Particularly, we developed an index, <i>D</i>, which enables to take into consideration a successive coefficient of variance (CV) over replicates and simulation years. The comparison between the number of replicates and the burn-in periods determined by <i>D</i> and those chosen by CV was performed. (3) Results: When only a single pattern was used to determine the number of replicates and the burn-in periods, the results varied depending on the pattern. (4) Conclusions: As multiple scale space-time patterns were used for the purposes, the simulated outputs after the burn-in periods with a proper number of replicates would well reproduce multiple patterns of phenomena. The outputs may also be more useful for hypothesis testing and validation. |
| first_indexed | 2024-03-10T07:36:49Z |
| format | Article |
| id | doaj.art-824434e6c01241a28e0c11eeb336f7a5 |
| institution | Directory Open Access Journal |
| issn | 2220-9964 |
| language | English |
| last_indexed | 2024-03-10T07:36:49Z |
| publishDate | 2021-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | ISPRS International Journal of Geo-Information |
| spelling | doaj.art-824434e6c01241a28e0c11eeb336f7a52023-11-22T13:25:03ZengMDPI AGISPRS International Journal of Geo-Information2220-99642021-09-0110960410.3390/ijgi10090604Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease TransmissionJeon-Young Kang0Jared Aldstadt1Department of Geography Education, Kongju National University, Gongju-si 314-701, KoreaDepartment of Geography, State University of New York at Buffalo, Buffalo, NY 14261, USA(1) Background: The stochastic nature of agent-based models (ABMs) may be responsible for the variability of simulated outputs. Multiple simulation runs (i.e., replicates) need to be performed to have enough sample size for hypothesis testing and validating simulations. The simulation outputs in the early-stage of simulations from non-terminating ABMs may be underestimated (or overestimated). To avoid this initialization bias, the simulations need to be run for a burn-in period. This study proposes to use multiple scale space-time patterns to determine the number of required replicates and burn-in periods in spatially explicit ABMs, and develop an indicator for these purposes. (2) Methods: ABMs of vector-borne disease transmission were used as the case study. Particularly, we developed an index, <i>D</i>, which enables to take into consideration a successive coefficient of variance (CV) over replicates and simulation years. The comparison between the number of replicates and the burn-in periods determined by <i>D</i> and those chosen by CV was performed. (3) Results: When only a single pattern was used to determine the number of replicates and the burn-in periods, the results varied depending on the pattern. (4) Conclusions: As multiple scale space-time patterns were used for the purposes, the simulated outputs after the burn-in periods with a proper number of replicates would well reproduce multiple patterns of phenomena. The outputs may also be more useful for hypothesis testing and validation.https://www.mdpi.com/2220-9964/10/9/604agent-based modelingmultiple scale space-time patternsample sizeburn-in periodsvector-borne disease |
| spellingShingle | Jeon-Young Kang Jared Aldstadt Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission ISPRS International Journal of Geo-Information agent-based modeling multiple scale space-time pattern sample size burn-in periods vector-borne disease |
| title | Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission |
| title_full | Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission |
| title_fullStr | Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission |
| title_full_unstemmed | Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission |
| title_short | Using Multiple Scale Space-Time Patterns to Determine the Number of Replicates and Burn-In Periods in Spatially Explicit Agent-Based Modeling of Vector-Borne Disease Transmission |
| title_sort | using multiple scale space time patterns to determine the number of replicates and burn in periods in spatially explicit agent based modeling of vector borne disease transmission |
| topic | agent-based modeling multiple scale space-time pattern sample size burn-in periods vector-borne disease |
| url | https://www.mdpi.com/2220-9964/10/9/604 |
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