Results 271 to 280 of about 103,075 (296)

Bayesian derivation of Akaike's information criterion

1991
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Akaike Information Criterion

2022
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Akaike’s Information Criterion (AIC) and the Third Variance

2013
One statistic in selecting a multiple regression equation is Mallows’ C p , which is an approximation of the error variance of the estimates given by a multiple regression equation. This error variance multiplied by n is written as $$\displaystyle\begin{array}{rcl} E{\Bigl [\sum _{i=1}^{n}{(\hat{y}_{ i} - E[y_{i}])}^{2}\Bigr ]}& =& E{\Bigl [{\bigl (
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Akaike's information criterion and Schwarz's criterion [PDF]

Stata Technical Bulletin, 1999
Aurelio Tobias, Michael J. Campbell
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Uninformative Parameters and Model Selection Using Akaike's Information Criterion

Journal of Wildlife Management, 2010
Todd W Arnold
exaly   +2 more sources

Akaike's information criterion

2001
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Akaike Information Criterion Statistics

Technometrics, 1989
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Model selection and Akaike's Information Criterion (AIC): The general theory and its analytical extensions

Psychometrika, 1987
Hamparsum Bozdogan, Bozdogan Hamparsum
exaly  

Akaike’s Information Criterion

2011
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Akaike's Information Criterion

2012
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