BIC and QBIC
BIC or QBIC are alternative model selection metrics to AICc or QAICc. The number of parameters in the model is K. The BIC depends on the number of parameters as
BIC = -2log Likelihood + K*log(n-ess)
and as does the QBIC (quasi-BIC)
QBIC = -2log Likelihood/c-hat + K*log(n-ess) ,
where n-ess is the effective sample size.
You can change the QBIC value by changing c-hat with the Adjustments | c-hat menu options from the Results Browser.
The default in MARK is to use AICc or QAICc, but you can use the BIC model selection parameter by selecting the BIC option in the File | Preferences window.
Model weights and model likelihood are also computed using BIC instead of AICc, so that model averaging is also conducted from the BIC.