Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes

We develop a new split-step θ (SSθ) method for stochastic age-dependent capital system with random jump magnitudes. The main aim of this paper is to investigate the convergence of the SSθ method for a class of stochastic age-dependent capital system with random jump magnitudes. It is proved that the...

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Main Authors: Jianguo Tan, A. Rathinasamy, Hongli Wang, Yongfeng Guo
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Abstract and Applied Analysis
Online Access:http://dx.doi.org/10.1155/2014/791048
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author Jianguo Tan
A. Rathinasamy
Hongli Wang
Yongfeng Guo
author_facet Jianguo Tan
A. Rathinasamy
Hongli Wang
Yongfeng Guo
author_sort Jianguo Tan
collection DOAJ
description We develop a new split-step θ (SSθ) method for stochastic age-dependent capital system with random jump magnitudes. The main aim of this paper is to investigate the convergence of the SSθ method for a class of stochastic age-dependent capital system with random jump magnitudes. It is proved that the proposed method is convergent with strong order 1/2 under given conditions. Finally, an example is simulated to verify the results obtained from theory.
format Article
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institution DOAJ
issn 1085-3375
1687-0409
language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series Abstract and Applied Analysis
spelling doaj-art-137aac2195da4e2c87460dea3daf3df72025-08-20T03:17:02ZengWileyAbstract and Applied Analysis1085-33751687-04092014-01-01201410.1155/2014/791048791048Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump MagnitudesJianguo Tan0A. Rathinasamy1Hongli Wang2Yongfeng Guo3Department of Mathematics, Tianjin Polytechnic University, Tianjin 300387, ChinaDepartment of Mathematics, PSG College of Technology, Coimbatore 641004, IndiaDepartment of Mechanics, Tianjin University, Tianjin 300072, ChinaDepartment of Mathematics, Tianjin Polytechnic University, Tianjin 300387, ChinaWe develop a new split-step θ (SSθ) method for stochastic age-dependent capital system with random jump magnitudes. The main aim of this paper is to investigate the convergence of the SSθ method for a class of stochastic age-dependent capital system with random jump magnitudes. It is proved that the proposed method is convergent with strong order 1/2 under given conditions. Finally, an example is simulated to verify the results obtained from theory.http://dx.doi.org/10.1155/2014/791048
spellingShingle Jianguo Tan
A. Rathinasamy
Hongli Wang
Yongfeng Guo
Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
Abstract and Applied Analysis
title Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
title_full Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
title_fullStr Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
title_full_unstemmed Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
title_short Strong Convergence of the Split-Step θ-Method for Stochastic Age-Dependent Capital System with Random Jump Magnitudes
title_sort strong convergence of the split step θ method for stochastic age dependent capital system with random jump magnitudes
url http://dx.doi.org/10.1155/2014/791048
work_keys_str_mv AT jianguotan strongconvergenceofthesplitstepthmethodforstochasticagedependentcapitalsystemwithrandomjumpmagnitudes
AT arathinasamy strongconvergenceofthesplitstepthmethodforstochasticagedependentcapitalsystemwithrandomjumpmagnitudes
AT hongliwang strongconvergenceofthesplitstepthmethodforstochasticagedependentcapitalsystemwithrandomjumpmagnitudes
AT yongfengguo strongconvergenceofthesplitstepthmethodforstochasticagedependentcapitalsystemwithrandomjumpmagnitudes