Open AccessThe Volatility of Data Space: Topology Oriented Sensitivity Analysis
Author(s) -
Jing Du,
Arika Ligmann-Zielińska
Publication year - 2015
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0137591
Subject(s) - sensitivity (control systems) , topology (electrical circuits) , topological data analysis , volatility (finance) , computer science , space (punctuation) , data space , data mining , mathematics , algorithm , econometrics , artificial intelligence , engineering , combinatorics , electronic engineering , operating system
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.