IMPROVED ESTIMATION OF THE EXPECTED KULLBACK–LEIBLER DISCREPANCY IN CASE OF MISSPECIFICATION
模型误设下期望 Kullback–Leibler 差异的改进估计
In case of misspecification, the Akaike information criterion (AIC; Akaike, 1973, in Petrov & Csaki, eds., Second International Symposium on Information Theory, pp. 267–281. Budapest: Akademia Kiado) is an asymptotically biased estimator of the expected Kullback–Leibler discrepancy. This paper gives simple expressions for the bias that can be used to construct improved estimators. However, for the examples that are considered in detail it turns out that model selection…