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Derivation of the most critical attribute in a complex risk management system
Leading article: 2018. June (MIAU No. 238.)
(Previous article: MIAU No. 237.)
Keywords: bubble, production function, static-dynamic approach, similarity analysis
Abstract: The attributes needing a specific handling can be derived in different static and dynamic
ways. In both cases, production functions should be generated. In a static approach, the production
functions should have stairs (c.f. staircase functions) in order to be capable of interpretations of
general and/or constellation-specific impacts of attributes compared to each other. In a dynamic case,
production functions need time series as inputs and in this case each X-attribute should be modelled
as Y. A model for the original Y-attribute may lead to estimation errors, which can be interpreted as a
kind of bubble-effect. In case of parallel Y-attributes, the amount of these bubble effects can be seen
as information about ranking of the analyzed Y-attributes according to the detected volume of
exposures. If each X-attributes will be modelled as Y, the most specific attribute is the attribute, where
the differences between the estimated and the real values lead to the highest error value, because the
X-attributes being interpretable build a kind of consistent frame.
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