Simulating Discounted Costs
Author(s) -
Bennett L. Fox,
Peter W. Glynn
Publication year - 1989
Publication title -
management science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.954
H-Index - 255
eISSN - 1526-5501
pISSN - 0025-1909
DOI - 10.1287/mnsc.35.11.1297
Subject(s) - truncation (statistics) , estimator , variance (accounting) , mathematical optimization , horizon , markov chain , time horizon , mathematics , computer science , economics , statistics , geometry , accounting
We numerically estimate, via simulation, the expected infinite-horizon discounted cost d of running a stochastic system. A naive strategy estimates a finite-horizon approximation to d. We propose alternatives. All are ranked with respect to asymptotic variance as a function of computer-time budget and discount rate, when semi-Markov and/or regenerative structure or neither is assumed. In this setting, the naive truncation estimator loses; it may triumph, however, when the computer-time budget is modest, the discount rate is large, and the process simulated is not regenerative or has long cycle lengths.discounted costs, simulation, semi-Markov process, regenerative process
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