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AIC Under the Framework of Least Squares Estimation

In this note we explain the use of the Akiake Information Criterion and its related model comparison indices (usually derived for maximum likelihood estimator inverse problem formulations) in the context of least squares (ordinary, weighted, iterative weighted or “generalized”, etc.) based inverse problem formulations. The ideas are illustrated with several examples of interest in biology.

Identiferoai:union.ndltd.org:ETSU/oai:dc.etsu.edu:etsu-works-11780
Date01 December 2017
CreatorsBanks, H. T., Joyner, Michele L.
PublisherDigital Commons @ East Tennessee State University
Source SetsEast Tennessee State University
Detected LanguageEnglish
Typetext
SourceETSU Faculty Works

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