Derivatives of Markov Kernels and Their Jordan Decomposition
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Publication:3527976
DOI10.1515/JAA.2008.13zbMath1159.60027OpenAlexW2173079091MaRDI QIDQ3527976
Arie Hordijk, Heinz Weisshaupt, Bernd F. Heidergott
Publication date: 1 October 2008
Published in: Journal of Applied Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1515/jaa.2008.13
Differentiation (real functions of one variable): general theory, generalized derivatives, mean value theorems (26A24) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Abstract differentiation theory, differentiation of set functions (28A15) Kernel operators (47B34)
Related Items (4)
Gradient estimation for smooth stopping criteria ⋮ On the differentiability of parametrized families of linear operators and the sensitivity of their stationary vectors ⋮ Measure-valued differentiation for Markov chains ⋮ Taylor series expansions for stationary Markov chains
Cites Work
- A characterization of parallelepipeds related to weak derivatives
- A generalization of Lehmann's theorem on the comparison of uniform location experiments
- A weak derivative approach to optimization of threshold parameters in a multicomponent maintenance system
- OPTION PRICING VIA MONTE CARLO SIMULATIONA WEAK DERIVATIVE APPROACH
- Probability Gradient Estimation by Set-Valued Calculus and Applications in Network Design
- Measure-Valued Differentiation for Stationary Markov Chains
- A measure-valued approach to convex set-valued dynamics
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