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In the rest of this paper, we consider the PDF of for the multiple candidate case.
However, for the multiple candidate case, since the amplitude of the selected candidate is not Rayleigh distributed, such as (8), this Gaussian assumption no longer holds.
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Note that in [13], the authors used the Rayleigh PDF (single candidate) for obtaining the error performance of multiple candidate cases.
In the case of multiple candidate process models, model discrimination is then performed to choose the best representative one by comparing posterior probability shares.
In those cases where multiple candidate structures exist, ACD/Structure Elucidator is equipped to validate the correct structure and eliminate inconsistent candidates.
The cases with multiple candidate variables are solved by judgment.
In cases where multiple candidate codes were present, we recorded only the first-listed code.
In cases where multiple candidate full-length assemblies existed, we chose the entry with the longest complete ORF.
In cases where multiple candidate models had Δ AICc of ≤2, the model with the fewest variables was selected as the most parsimonious model.
In this analysis we apply multiple candidate outbreak definitions to reported dengue case data from Brazil to test this assumption.
Where there are multiple candidate pharmacologic biomarkers as is the case with tipifarnib, a comprehensive, parallel study of all candidates is required.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com