A Note on Bayes Factors for Log-Linear Contingency Table Models with Vague Prior Information
本文指出Spiegelhalter和Smith提出的近似贝叶斯因子在零频数时无法计算，而使用Jeffreys先验可解决此问题，并说明该贝叶斯因子在大样本下近似等价于Schwarz模型选择准则。
SUMMARY The approximate Bayes factor, B 01, for log-linear contingency table models proposed by Spiegelhalter and Smith (1982) is indeterminate if any of the cell frequencies is zero. It is noted that use of a standard Jeffreys prior overcomes this difficulty. It is pointed out that – 2 log B 01 is approximately equivalent to Schwarz's (1978) model selection criterion in large samples.