Sentence examples for better fitting models from inspiring English sources

26 The AIC, BIC and SSABIC indicate relative goodness of fit; lower values represent better fitting models.

The AIC is a relative measure of information lost when fitting the model; hence, smaller AIC values suggest better fitting models.

Differences in BIC can be used to compare competing models, with better fitting models having smaller BIC values.

Fitting a spatial component to the error variance, as we have done here, has been found to give better fitting models for many forestry trials and traits than when modelling only replicate and block effects (Dutkowski et al. [2002], [2006]; Dungey et al. [2012]).

Lower AIC and BIC values suggest better fitting models.

Lower values reflect better fitting models.

Bayes information criteria [BIC; 33] were used to decide on the fit of non-nested models; smaller values of BIC indicated a better fitting model.

Although confidence intervals based on observed information are unbiased asymptotically [ 37], it appeared that for the models investigated here fitted to the datasets used for illustration, and particularly for a better fitting model, they could not be relied upon.

The Akaike Information Criterion (AIC) is a statistic generally used to compare the fit of non-nested or non-hierarchical models; lower values indicate a better fitting model.

The Akaike Information Criterion (AIC) was used for model comparisons; smaller values indicate better fitting model.

The context-dependent acoustic models provide better fitting modeling and this is shown by the consistent increase in the results.