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Statistical model evaluation and information criteria. (English) Zbl 0941.62002
Ghosh, Subir (ed.), Multivariate analysis, design of experiments, and survey sampling. A tribute to Jagdish N. Srivastava. New York, NY: Marcel Dekker. Stat., Textb. Monogr. 159, 369-399 (1999).
From the introduction: The main aim of the present paper is to give a systematic account of some recent developments in model evaluation criteria from an information-theoretic point of view. Section 2 presents a unified information-theoretic approach to statistical model evaluation problems. We intend to provide a basic expository account of the fundamental principles behind information criteria. The use of the criteria is illustrated by examples. We also discuss the application of the bootstrap methods in model evaluation problems. In Section 3, the information criteria proposed are applied to the evaluation of the various types of models based on robust, maximum penalized likelihood. In Section 4 we give the derivation of information criteria and investigate their asymptotic properties with theoretical and numerical improvements.
For the entire collection see [Zbl 0927.00053].

MSC:
62B10 Statistical aspects of information-theoretic topics
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