The Volatility of Data Space: Topology Oriented Sensitivity Analysis
Authored by Arika Ligmann-Zielinska, Jing Du
Date Published: 2015
DOI: 10.1371/journal.pone.0137591
Sponsors:
United States National Science Foundation (NSF)
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Abstract
Despite the difference among specific methods, existing Sensitivity
Analysis (SA) technologies are all value-based, that is, the
uncertainties in the model input and output are quantified as changes of
values. This paradigm provides only limited insight into the nature of
models and the modeled systems. In addition to the value of data, a
potentially richer information about the model lies in the topological
difference between pre-model data space and post-model data space. This
paper introduces an innovative SA method called Topology Oriented
Sensitivity Analysis, which defines sensitivity as the volatility of
data space. It extends SA into a deeper level that lies in the topology
of data.
Tags
Agent-based model
Uncertainty
Land-use change