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This master thesis investigates the role of Akaike Information Criterion (AIC) in choosing statistical models, combining theoretical foundations with practical simulations to evaluate its effectiveness. The theoretical part of the thesis shows that AIC is based on Kullback-Leibler divergence and cross-entropy, emphasizing its role in minimizing ...
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Bootstrapping Log Likelihood and EIC, an Extension of AIC
Annals of the Institute of Statistical Mathematics, 1997Genshiro Kitagawa
exaly
A Stepwise AIC Method for Variable Selection in Linear Regression
Communications in Statistics - Theory and Methods, 2007Ryotaro Kamimura
exaly
American Journal of Obstetrics and Gynecology, 1981
Herbert C. Schwartz +2 more
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Herbert C. Schwartz +2 more
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Model selection of copulas: AIC versus a cross validation copula information criterion
Statistics and Probability Letters, 2014Lars Arne Jordanger
exaly
The T cell-selective IL-2 mutant AIC284 mediates protection in a rat model of Multiple Sclerosis
Journal of Neuroimmunology, 2015Niklas Beyersdorf
exaly