Motivated by their ability to mimic complex biological and natural processes, many spatially explicit models (SEMs) have been proposed during the last two decades for simulating such processes. Yet, a sensitivity analysis (SA) of such models is typically not performed, or model sensitivity is only studied over time on the basis of aggregated quantities, due to the lack of an appropriate framework. Taking a SEM for myxomatosis among European rabbits in Belgium as a model SEM, we conduct a spatial SA and investigate to what extent the sensitivity of this model varies spatially and whether or not this should become common practice when developing a SEM.
CITATION STYLE
Baetens, J. M., & De Baets, B. (2016). A spatial sensitivity analysis of a spatially explicit model for myxomatosis in Belgium. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 9863 LNCS, 91–100. https://doi.org/10.1007/978-3-319-44365-2_9
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