Sentence examples for model comparison criterion from inspiring English sources

The method used a model comparison criterion analogous to that of Manichaikul et al. (2009).

As stated before, AUC measures predictive ability and may be considered as a model comparison criterion.

The AUC can be used as a model comparison criterion and can be interpreted as the probability that a given classifier assigns a higher score to a positive example than to a negative one, when the positive and negative examples are randomly picked.

B I C = 2 (L C N A + L B A F + L S N V ) − k log (L C N A + L B A F + L S N V ) k ≡ (c m a x + 1 ) n + N s (n + 1 ) Additionally, the goodness of fit (the average geometrical distance of data points to the model prediction) can also be used as a model comparison criterion and is included in the output.

For model comparison three criteria, namely loglikelihood, Akaike information criterion (AIC) and Bayesian information criterion (BIC) are calculated.

Two samples of 163 and 68 programs were used for verifying and validating respectively the models; the comparison criterion was the Mean Magnitude of Error Relative to the estimate (MMER).

Model comparison using Akaike information criterion (AIC).

Using simulations under heterotachous conditions, we explore the properties of three model comparison methods: the Akaike information criterion, the Bayesian information criterion, and cross validation.

Akaike Information Criterion multivariate model comparison found that relative PSA was a better predictor of positive PET/CT than trigger PSA (PSAt).

To improve convergence, the between-study variance could be determined by non-iterative methods [24], but these approaches are difficult to combine with the maximum likelihood approach for estimating the weight function, and with model comparison based on the Akaike criterion.

A stepwise model comparison and Akaike's information criterion were used to determine the best model for multivariate analysis.