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Akaike information criterion

Known as: Information criterion, Akaike, AICc 
The Akaike information criterion (AIC) is a measure of the relative quality of statistical models for a given set of data. Given a collection of… Expand
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Highly Cited
2014
Highly Cited
2014
 
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Highly Cited
2011
Highly Cited
2011
  • Hirotugu Akaike
  • International Encyclopedia of Statistical Science
  • 2011
  • Corpus ID: 43739288
 
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Highly Cited
2010
Highly Cited
2010
Akaike’s information criterion (AIC) is increasingly being used in analyses in the field of ecology. This measure allows one to… Expand
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Highly Cited
2010
Highly Cited
2010
In regular statistical models, the leave-one-out cross-validation is asymptotically equivalent to the Akaike information… Expand
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Highly Cited
2006
Highly Cited
2006
Abstract Variations in environmental variables and measurement errors often result in large and heterogeneous variations in… Expand
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Highly Cited
1998
Highly Cited
1998
Summary. Many different methods have been proposed to construct nonparametric estimates of a smooth regression function… Expand
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Highly Cited
1986
Highly Cited
1986
In 1983, Horowitz proposed the use of an adjusted likelihood ratio index to select between alternative models. We define an… Expand
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Highly Cited
1985
Highly Cited
1985
We extend the standard finance model of the firm's dividend/investment/financing decisions by allowing the firm's managers to… Expand
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Highly Cited
1978
Highly Cited
1978
Using Akaike's information criterion, three examples of statistical data are reanalyzed and show reasonably definite conclusions… Expand
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Highly Cited
1978
Highly Cited
1978
The number of digits it takes to write down an observed sequence x1,...,xN of a time series depends on the model with its… Expand
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