Description
Statistical model selection using the Akaike Information Criterion (AIC) and similar criteria is a useful tool for comparing multiple and non-nested models without the specification of a null model, which has made it increasingly popular in the natural and social sciences.
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Contributors
- Cullan, Michael J (Author)
- Sterner, Beckett (Thesis advisor)
- Fricks, John (Committee member)
- Kao, Ming-Hung (Committee member)
- Arizona State University (Publisher)
Date Created
The date the item was original created (prior to any relationship with the ASU Digital Repositories.)
2018
Resource Type
Collections this item is in
Note
- Partial requirement for: M.S., Arizona State University, 2018Note typethesis
- Includes bibliographical references (pages 73-76)Note typebibliography
- Field of study: Statistics
Citation and reuse
Statement of Responsibility
by Michael J. Cullan