Modeling Dependency Structure for AEC Measurement Using Belief Function and PBVAR Approach
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文摘
The main purpose of this paper is to test the of expectation functions for decision making by investigating the concept subjective probability under measurable risk events as suggested by Dempster-Shafer theory. The experiment illustrated the use of modelling dependency structure for AEC measurement using belief function and PBVAR Approach. On the main objective origination, the economic evidences were calculated to support economic phenomena consist of the world economic growth and AEC economic growth. The growth rate terms of GDP, FDI, Stock Market, and Labour force for selected Asian economies covered the period from 1998 to 2014 were tested. From these evidences, the mass function of belief function and the plausibility function so called the low-mass regime and high-mass regime of the cluster mass function are calculated that encompasses both economic expansion and economic recession. The experimental evidence to identify how to use such a model to plan for a financial assessment where management fraud risk is assessed to be high. Furthermore, one source of further information about econometric methodologies for measuring the results of the economic evidences and for assessments the effect of public and private sector growth encompassing both economic expansion and economic recession. The approach illustrated in this paper where a parallel, but separate, assessment is made of AEC economic expansion and AEC economic recession.
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