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dc.contributor.author차지환*
dc.date.accessioned2016-08-28T10:08:21Z-
dc.date.available2016-08-28T10:08:21Z-
dc.date.issued2013*
dc.identifier.issn0378-3758*
dc.identifier.otherOAK-9698*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/223377-
dc.description.abstractUsually, two different types of shock models (extreme and cumulative shock models) are employed to model the dynamic risk processes. In extreme shock models, only the impact of the current fatal shock is usually taken into account, whereas, in cumulative shock models, the impact of the preceding shocks is accumulated as well. However, in practice, the effect of the corresponding shock can be realized in those two ways in one model (i.e., it can be fatal or, otherwise it is accumulated). This observation justifies the consideration of a 'combined shock model' in the risk modeling and analysis. In this paper, we generalize the study of the dynamic risk processes that were previously considered in the literature. The main theme of this paper is to find the optimal allocation policies for the generalized combined risk processes via the stochastic comparisons of survival functions. It will be seen that the obtained results hold for 'general counting processes' of shocks. In addition, we consider the problem of maximizing a gain function under certain risks and obtain reasonable decisions based on a variability measure. Furthermore, the meaningful explanations for the results on the policy ordering will be provided. © 2012 Elsevier B.V.*
dc.languageEnglish*
dc.titleStochastic comparison of generalized combined risk processes*
dc.typeArticle*
dc.relation.issue4*
dc.relation.volume143*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.startpage818*
dc.relation.lastpage826*
dc.relation.journaltitleJournal of Statistical Planning and Inference*
dc.identifier.doi10.1016/j.jspi.2012.10.012*
dc.identifier.wosidWOS:000314198700014*
dc.identifier.scopusid2-s2.0-84871524224*
dc.author.googleCha J.H.*
dc.contributor.scopusid차지환(7202455739)*
dc.date.modifydate20231123095848*
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자연과학대학 > 통계학전공 > Journal papers
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