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Model selection

In developing an understanding of real-world problems,
researchers develop mathematical and statistical models. Various
model selection methods exist which can be used to obtain a
mathematical model that best describes the real-world situation
in some or other sense. These methods aim to assess the merits
of competing models by concentrating on a particular criterion.
Each selection method is associated with its own criterion and
is named accordingly. The better known ones include Akaike's
Information Criterion, Mallows' Cp and cross-validation, to name
a few. The value of the criterion is calculated for each model
and the model corresponding to the minimum value of the criterion
is then selected as the "best" model. / Mathematical Sciences / M. Sc. (Statistics)

Identiferoai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:unisa/oai:umkn-dsp01.int.unisa.ac.za:10500/16951
Date11 1900
CreatorsHildebrand, Annelize
ContributorsFresen, J. L.
Source SetsSouth African National ETD Portal
LanguageEnglish
Detected LanguageEnglish
TypeDissertation
Format1 online resource (81 leaves)

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