Results 191 to 200 of about 101,405 (230)

Properties of the Akaike information criterion

Microelectronics Reliability, 1996
The paper gives the origins of AIC and discusses the main properties of this measure when it is applied to continuous and discrete models. It is illustrated that AIC is not a measure of informativity because it fails to have some expected properties of information measures.
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On the Comparison of Akaike Information Criterion and Consistent Akaike Information Criterion in Selection of an Asymmetric Price Relationship: Bootstrap Simulation Results

2013
Akaike’s Information Criteria provide a basis for choosing between competing approaches to testing for price asymmetry. However, very little research has been undertaken to understand its performance in the price transmission modelling context. In addressing this issue, this paper introduces and applies parametric bootstrap techniques to evaluate the ...
Acquah, H. De-Graft, Acquah, H. De-Graft
openaire   +3 more sources

The Akaike Information Criterion with Parameter Uncertainty

Fourth IEEE Workshop on Sensor Array and Multichannel Processing, 2006., 2006
An instance crucial to most problems in signal processing is the selection of the order of a candidate model. Among the different exciting criteria, the two most popular model selection criteria in the signal processing literature have been the Akaike's criterion AIC and the Bayesian information criterion BIC. These criteria are similar in form in that
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Conditional Akaike information criterion in the Fay–Herriot model

Statistical Methodology, 2013
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The Akaike information criterion: Background, derivation, properties, application, interpretation, and refinements

WIREs Computational Statistics, 2019
The Akaike information criterion (AIC) is one of the most ubiquitous tools in statistical modeling. The first model selection criterion to gain widespread acceptance, AIC was introduced in 1973 by Hirotugu Akaike as an extension to the maximum likelihood
Joseph E. Cavanaugh, A. Neath
semanticscholar   +1 more source

Akaike Information Criterion Statistics.

Journal of the Royal Statistical Society. Series A (Statistics in Society), 1988
Daniel G. Brooks, Y. Sakamoto, M. Ishiguro, G. Kitagawa   +3 more
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A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion

Behavioral Ecology and Sociobiology, 2010
M. Symonds, A. Moussalli
semanticscholar   +1 more source

Application of Akaike's information criterion (AIC) in the evaluation of linear pharmacokinetic equations

Journal of pharmacokinetics and biopharmaceutics, 1978
K. Yamaoka, T. Nakagawa, T. Uno
semanticscholar   +1 more source

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

, 1987
H. Bozdogan
semanticscholar   +1 more source

Uninformative Parameters and Model Selection Using Akaike's Information Criterion

, 2010
T. Arnold
semanticscholar   +1 more source