Sentence examples for model comparison used from inspiring English sources

Model comparison used Kullback-Leibler information to assign relative strength of evidence (Akaike's Information Criterion corrected for small samples [AICc, 26, 35]) to each model in the set [ 26].

In addition to just comparing the small samples of neurons that were classified as matched vs mismatched congruency, we now perform a model comparison using the data from all 127 pairs of neurons, which gives us substantially greater power.

Thirdly, model comparison using posterior predictive p-values will be discussed in detail to identify the existence of dark sources in the population.

Model comparison using the Akaike Information Criterion (AIC), the Schwarz Bayseian Information Criterion (BIC) and the Bayes Factor allows direct comparison of model results irrespective of the number of model parameters.

a, Bayesian model comparison using BIC scores revealed that the Maintain model explained the data better than a Decay model in which a free parameter captured how much the animals would 'forget' the unavailable option as well as two risk-sensitive models where the probabilities could be distorted by the animals.

An unconstrained graded response model (GRM) and a Rasch Model were fitted to estimate indices for model comparison using likelihood ratio (LR) test and information criteria.

In contrast, the standard deviation estimated by a single model, which was also used in the multiple model comparison using three different land-use datasets, was 0.27 PgC year−1 (Jain et al. [2013]).

Furthermore, we also performed a simulation study, assessing the veracity of parameter estimation and model comparison using synthetic data for which the ground truth was known.

Adult survival clearly varied between habitat types as a model with constant (habitat-independent) survival and transition probabilities Sp received much lower support than the habitat-dependent model S[hab]pψ [hab] (based on model comparison using Akaike's Information Criterion corrected for effective sample size AICc [46], difference between AICc values Δ AICc = 90.4).

Model comparison using Akaike information criterion (AIC).

Model comparison using the Negative Frequency-Dependent Selection model (NFDS).