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When truncated at optimal order ("superasymptotic" approximation), the series gives no information about the radiation coefficient α (except order-of-magnitude) because the absolute error is O.
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This is because the values of the absolute error for these methods are effectively given by their Monte Carlo error, rather than the bias (this is a recurring theme in stochastic simulations - see Section Monte Carlo error).
The adaptive log-likelihood surrogates based on the relative error indicators outperform those based on the absolute error indicators, because adaptation based on the relative error indicator puts more sparse-grid nodes in the areas in the parameter space where the log-likelihood is high.
However, the absolute error is worse because of the lack of a calibration sample having a well-known H content.
The absolute error reaches 0.12 and the relative error 30%.
Then, the absolute error and relative error are (35).
The absolute error is the absolute difference of the actual aggregate from the computed aggregate.
Figure 2 The absolute error of the obtained results.
The absolute error (Abs er ) is given by.
Difference shows the absolute error of ranging data.
As b deceases, the absolute error becomes very small.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com