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Ad-a 213 787 Likelihood Ratio Derivative Estimators for Stochastic Systems
| Content Provider | Semantic Scholar |
|---|---|
| Author | Glynn, Peter W. |
| Abstract | to specialize the general idea underlying this family of derivative estimators to the various classes of stochastic processes This paper discusses likelihood ratio derivative estimadescribed above. tion techniques for stochastic systems. After a brief review of the basic concepts, likelihood ratio derivative estimators 2. LIKELIHOOD RATIO DERIVATIVE are presented for the following classes of stochastic processes: time homogeneous discrete-time Markov chains, non-time hoESTIMATION mogeneous discretetime Markov chains, time komogeneous In this section, we provide a brief introduction to the continuouts-time Markov chains, semi-Markov processes, nontimehomogeneouscontinuous-time Mi, arkov pchns, ngnbasic ideas that underlie likelihood ratio derivative estimatime homogeneous continuous-time Markov chains, and generalized serni-Markv processes. ,1" tion. To set the stage, consider a family of stochastic syse tems that is indexed by a scalar decision parameter 0. For example in a queueing context, 0 might correspond to the |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://www.dtic.mil/dtic/tr/fulltext/u2/a213787.pdf |
| Alternate Webpage(s) | https://www.researchgate.net/profile/Peter_Glynn2/publication/221527637_Likelihood_ratio_derviative_estimators_for_stochastic_systems/links/00b7d5178a66002905000000.pdf |
| Alternate Webpage(s) | https://www.researchgate.net/profile/Peter_Glynn2/publication/221527637_Likelihood_ratio_derviative_estimators_for_stochastic_systems/links/00b7d5178a66002905000000.pdf?inViewer=0&origin=publication_detail&pdfJsDownload=0 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
