<p>Reported are the average values of BIC over all subjects (mean±s.e.m.) and <i>p</i>-values for comparisons of BIC values between each model and its object-based or feature-based counterparts (two-sided Wilcoxon signed-rank test). The overall best model (feature-based or object-based with decay) and its object-based or feature-based counterpart are highlighted in cyan and brown, respectively.</p
This paper presents a refinement of the Bayesian Information Criterion (BIC). While the original BIC...
We develop a generalized Bayesian information criterion for regression model selection. The new crit...
In the signal processing literature, many methods have been pro-posed for solving the important mode...
<p>Bayesian information criterion (BIC) values are compared between several sub-models of the RDM. E...
Comparison of fitness of models based on Akaike information criterion (AIC) and Bayesian Information...
The Bayesian Information Criterion (BIC) is widely used for variables election in mixed effects mode...
AIC and BIC values shown here are relative to the intercept-only model. Therefore, negative numbers ...
(A) Comparison of the Bayesian information criterion (BIC) relative to the baseline model. Negative ...
<p>Log likelihoods (LL), Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC)...
In both cases, the number of parameters in the BIC formula is the the number of singular vectors ret...
Bayesian model averaging (BMA) is a widely used method for model and variable selection. In particul...
AIC: Akaike information criterion; PEP: protected exceedance probability; BIC: Bayesian information ...
<p>Clustering of the subscales showed stable results with an optimum of four clusters in both female...
Introduction The "Bayesian information criterion" (BIC) can be a helpful statistical tool ...
<p>BIC, Bayesian information criterion; <i>β</i>, cross-transmission coefficient; <i>ν</i>, sporadic...
This paper presents a refinement of the Bayesian Information Criterion (BIC). While the original BIC...
We develop a generalized Bayesian information criterion for regression model selection. The new crit...
In the signal processing literature, many methods have been pro-posed for solving the important mode...
<p>Bayesian information criterion (BIC) values are compared between several sub-models of the RDM. E...
Comparison of fitness of models based on Akaike information criterion (AIC) and Bayesian Information...
The Bayesian Information Criterion (BIC) is widely used for variables election in mixed effects mode...
AIC and BIC values shown here are relative to the intercept-only model. Therefore, negative numbers ...
(A) Comparison of the Bayesian information criterion (BIC) relative to the baseline model. Negative ...
<p>Log likelihoods (LL), Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC)...
In both cases, the number of parameters in the BIC formula is the the number of singular vectors ret...
Bayesian model averaging (BMA) is a widely used method for model and variable selection. In particul...
AIC: Akaike information criterion; PEP: protected exceedance probability; BIC: Bayesian information ...
<p>Clustering of the subscales showed stable results with an optimum of four clusters in both female...
Introduction The "Bayesian information criterion" (BIC) can be a helpful statistical tool ...
<p>BIC, Bayesian information criterion; <i>β</i>, cross-transmission coefficient; <i>ν</i>, sporadic...
This paper presents a refinement of the Bayesian Information Criterion (BIC). While the original BIC...
We develop a generalized Bayesian information criterion for regression model selection. The new crit...
In the signal processing literature, many methods have been pro-posed for solving the important mode...