Information Gap Decision Analysis
Information Gap Analysis
All the figures below are generated using examples/model_analysis/infogap.jl
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Setup
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There are 4 uncertain observations at times t = [1,2,3,4]
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There are 4 possible models that can be applied to match the data
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y(t) = a * t + c
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y(t) = a * t^(1.1) + b * t + c
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y(t) = a * t^n + b * t + c
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y(t) = a * exp(t * n) + b * t + c
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There are 4 unknown model parameters with uniform prior probability functions:
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a = Uniform(-10, 10)
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b = Uniform(-10, 10)
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c = Uniform(-5, 5)
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n = Uniform(-3, 3)
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The model prediction for t = 5 is unknown and information gap prediction uncertainty needs to be evaluated
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The horizon of information gap uncertainty
h
is applied to define the acceptable deviations in the 4 uncertain observations.