Semi-Markov and reward fields

被引：1

作者：

Soltani, A. R. ^{[1
,2
]}

Ghasemi, H. ^{[3
]}

机构：

[1] Kuwait Univ, Coll Sci, Dept Stat & Operat Res, Kuwait, Kuwait

[2] Shiraz Univ, Coll Sci, Dept Stat, Shiraz, Iran

[3] Amirkabir Univ, Fac Math & Comp Sci, Tehran, Iran

来源：

STATISTICS & PROBABILITY LETTERS | 2014年 / 95卷

关键词：

Markov renewal fields; Markov renewal sequences; Semi Markov fields; Reward fields; Expected reward fields;

D O I：

10.1016/j.spl.2014.08.012

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

We introduce semi-Markov fields and provide formulations for the basic terms in the semi-Markov theory. In particular we define and consider a class of associated reward fields. Then we present a formula for the expected reward at any multidimensional time epoch. The formula is indeed new even for the classical semi-Markov processes. It gives the expected cumulative reward for fairly large classes of reward functions; in particular, it provides the formulas for the expected cumulative reward given in Masuda and Sumitau (1991), Soltani (1996) and Soltani and Khorshidian (1998). (C) 2014 Elsevier B.V. All rights reserved.

引用

页码：71 / 76

页数：6

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