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In statistics, the Hannan–Quinn information criterion (HQC) is a criterion for
model selection Model selection is the task of selecting a statistical model from a set of candidate models, given data. In the simplest cases, a pre-existing set of data is considered. However, the task can also involve the design of experiments such that the ...
. It is an alternative to
Akaike information criterion The Akaike information criterion (AIC) is an estimator of prediction error and thereby relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to e ...
(AIC) and Bayesian information criterion (BIC). It is given as : \mathrm = -2 L_ + 2 k \ln(\ln(n)), \ where ''L_'' is the log-likelihood, ''k'' is the number of
parameters A parameter (), generally, is any characteristic that can help in defining or classifying a particular system (meaning an event, project, object, situation, etc.). That is, a parameter is an element of a system that is useful, or critical, when ...
, and ''n'' is the number of
observations Observation is the active acquisition of information from a primary source. In living beings, observation employs the senses. In science, observation can also involve the perception and recording of data via the use of scientific instrument ...
. Burnham & Anderson (2002, p. 287) say that HQC, "while often cited, seems to have seen little use in practice". They also note that HQC, like BIC, but unlike AIC, is not an estimator of
Kullback–Leibler divergence In mathematical statistics, the Kullback–Leibler divergence (also called relative entropy and I-divergence), denoted D_\text(P \parallel Q), is a type of statistical distance: a measure of how one probability distribution ''P'' is different fr ...
. Claeskens & Hjort (2008, ch. 4) note that HQC, like BIC, but unlike AIC, is not asymptotically efficient; however, it misses the optimal estimation rate by a very small \ln(\ln(n)) factor. They further point out that whatever method is being used for fine-tuning the criterion will be more important in practice than the term \ln(\ln(n)), since this latter number is small even for very large n; however, the \ln(\ln(n)) term ensures that, unlike AIC, HQC is strongly consistent. It follows from the
law of the iterated logarithm In probability theory, the law of the iterated logarithm describes the magnitude of the fluctuations of a random walk. The original statement of the law of the iterated logarithm is due to A. Ya. Khinchin (1924). Another statement was given by A ...
that any strongly consistent method must miss efficiency by at least a \ln(\ln(n)) factor, so in this sense HQC is asymptotically very well-behaved. Van der Pas and Grünwald prove that model selection based on a modified Bayesian estimator, the so-called switch distribution, in many cases behaves asymptotically like HQC, while retaining the advantages of Bayesian methods such as the use of priors etc.


See also

*
Akaike information criterion The Akaike information criterion (AIC) is an estimator of prediction error and thereby relative quality of statistical models for a given set of data. Given a collection of models for the data, AIC estimates the quality of each model, relative to e ...
* Bayesian information criterion *
Deviance information criterion The deviance information criterion (DIC) is a hierarchical modeling generalization of the Akaike information criterion (AIC). It is particularly useful in Bayesian model selection problems where the posterior distributions of the models have been o ...
*
Focused information criterion In statistics, the focused information criterion (FIC) is a method for selecting the most appropriate model among a set of competitors for a given data set. Unlike most other model selection strategies, like the Akaike information criterion (AIC), ...
*
Shibata information criterion Shibata may refer to: Places * Shibata, Miyagi, a town in Miyagi Prefecture * Shibata District, Miyagi, a district in Miyagi Prefecture * Shibata, Niigata, a city in Niigata Prefecture ** Shibata Station (Niigata), a railway station in Niigata Pre ...


References

* Aznar Grasa, A. (1989). ''Econometric Model Selection: A New Approach'', Springer. * Burnham, K.P. and Anderson, D.R. (2002). ''Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach'', 2nd ed. Springer-Verlag. . * Claeskens, G. and Hjort, N.L. (2008). ''Model Selection and Model Averaging'', Cambridge. * Hannan, E. J., and B. G. Quinn (1979), "The Determination of the order of an autoregression", ''
Journal of the Royal Statistical Society The ''Journal of the Royal Statistical Society'' is a peer-reviewed scientific journal of statistics. It comprises three series and is published by Wiley for the Royal Statistical Society. History The Statistical Society of London was founded ...
, Series B'', 41: 190–195. * Van der Pas, S.L.; Grünwald, P.D. (2017). "Almost the best of three worlds." To appear in
Statistica Sinica
DOI 10.5705/ss.202016.0011, 2017. * Chen, C et al. ''Order Determination for Autoregressive Processes Using Resampling methods'' Statistica Sinica 3:1993, http://www3.stat.sinica.edu.tw/statistica/oldpdf/A3n214.pdf {{DEFAULTSORT:Hannan-Quinn information criterion Regression variable selection Model selection