What does BIC stand for?

Bayesian Information Criterion

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Samples in periodicals archive:

Akaike's information criterion (AIC), the Bayesian information criterion (BIC), and the focused information criterion (FIC) are explained and compared.

Model selection and model averaging

The segmentation of the audio data was made using the acoustic-change detection procedure based on the Bayesian Information Criterion (BIC), which was first proposed for the audio segmentation in [5] and improved by Tritschler and Gopinath in [27].

A system for speaker detection and tracking in audio broadcast news

In addition, the Bayesian Information Criterion BIC = -2LL + kLn(n) was also used, where n is the total number of observations (Burnham and Anderson, 2002).

Using an inverse-logistic model to describe growth increments of ...

We used the Bayesian Information Criterion (Hardin and Hilbe 2001) to determine which model best fit the data.

Reduced intellectual development in children with prenatal lead ...

with the likelihood ratio test), the Bayesian information criterion (BIC) was used to select the most plausible model (11,12): BIC = -2 log(ML) + k log(n), where ML was the maximized likelihood, k was the number of parameters in the model, and n was the number of observations (number of compounds).

Rift Valley fever in small ruminants, Senegal, 2003

Among various model selection criteria the one proposed by Schwartz [24], known as Schwartz Bayesian information criterion (SBC), is shown to outperform other alternatives [30].

Tax revenues and economic growth: an empirical investigation for ...

2 Segmentation of Video Streams Using the Bayesian Information Criterion The Bayesian Information Criterion (BIC) as the model selection criterion has been used in [5].

Action recognition in meeting videos using head trajectories and ...

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.

Interpreting posterior relative risk estimates in disease-mapping ...