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References in periodicals archive ?
Select a single best model from among [M.sub.0],..., [M.sub.p] using cross-validated prediction error, [C.sub.p] (Akaike information criterion or AIC), Bayesian information criterion, or adjusted [R.sup.2].
The tests of goodness of fit measured by Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) for the two models were also presented in Table 7.
The Schwarz Bayesian Information Criterion BIC=n.ln (SSE/n)+k.ln(n); where, n: the number of observations, SSE: Sum of square errors, k: the number of parameters
The most common information theory approaches are the Akaike information criterion (AIC) (Katsanevakis 2006) and the Bayesian information criterion (BIC) (Morales-Bojorquez et al.
Another modification of AIC is the Bayesian information criterion (BIC), which penalizes larger models.
The usual practice is to establish the regression or time series model, select the significant variables, the criteria to determine the optimal model is Akaike Information Criterion, Bayesian Information Criterion. But the debate focus is which kind of standards is best.
The averaging methods include equally weighted averages, medians, mean square error (MSE)-weighted averages, Bayesian model averages based on a Bayesian information criterion (BIC) approximation, and averages based on the top 10 percent of models that have performed best historically.
Akaike's information criterion (AIC), the Bayesian information criterion (BIC), and the focused information criterion (FIC) are explained and compared.
Such evaluation is usually carried out using some information criterion such as the Bayesian information criterion. In the context of large data sets this is not possible.
The Bayesian Information Criterion (BIC) as the model selection criterion has been used in [5].
Proposed methods include the Akaike Information Criteria (AIC) (Akaike 1973), the Information Complexity Criteria (ICOMP) (Bozdogan 1987), the Normalized Entropy of assessment (NEC) (Celeux and Soromenho 1996), and the Bayesian Information criterion (BSC) introduced by Schwarz (1978).
(2000) compared a number of models that could be used for disease mapping by goodness of fit criteria that included correlation between the simulated map and the smoothed map and a Bayesian information criterion. They concluded that the version of the CAR model proposed by Besag et al.
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