Abstract
We establish sufficient conditions for differentiability of the expected cost collected over a discrete-Time Markov chain until it enters a given set. The parameter with respect to which differentiability is analysed may simultaneously affect the Markov chain and the set defining the stopping criterion. The general statements on differentiability lead to unbiased gradient estimators.
| Original language | English |
|---|---|
| Pages (from-to) | 29-55 |
| Number of pages | 27 |
| Journal | Advances in Applied Probability |
| Volume | 55 |
| Issue number | 1 |
| Early online date | 15 Jun 2022 |
| DOIs | |
| Publication status | Published - Mar 2023 |
Bibliographical note
Publisher Copyright:© The Author(s), 2022. Published by Cambridge University Press on behalf of Applied Probability Trust.
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- gradient estimation
- Monte Carlo simulation
- Sensitivity analysis
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