On measures of information and divergence and model selection criteria

被引：1
|
作者：
Karagrigoriou, Alex [1 ]
Papaioannou, Takis [2 ,3 ]
机构：
[1] Univ Cyprus, Dept Math & Stat, POB 20537, CY-1678 Nicosia, Cyprus
[2] Univ Piraeus, Dept Stat & Insurance Sci, Piraeus, Greece
[3] Univ Ioannina, Dept Math, GR-45110 Ioannina, Greece
来源：
STATISTICAL MODELS AND METHODS FOR BIOMEDICAL AND TECHNICAL SYSTEMS | 2008年
关键词：
measures of information and divergence; acid-test; additivity property; weighted distribution; censoring and truncation; model selection; AIC; DIC;
D O I：
10.1007/978-0-8176-4619-6_35
中图分类号：
O29 [应用数学];
学科分类号：
070104 ;
摘要：
In this chapter we discuss measures of information and divergence and model selection criteria. Three classes of measures, Fisher-type, divergence-type, and entropy-type measures, are discussed and their properties are presented. Information through censoring and truncation is presented and model selection criteria are investigated including the Akaike information criterion (AIC) and the divergence information criterion (DIC).
引用
收藏
页码：503 / +
页数：4
相关论文
共 50 条
12345