Approximating Markov Chains for Bootstrapping and Simulation

DOI10.1007/978-3-319-13881-7_41zbMath1351.62082OpenAlexW390005907MaRDI QIDQ2833388

Cristian Pelizzari, G. Guastaroba, Paolo Falbo, Roy Cerqueti

Publication date: 18 November 2016

Published in: Springer Proceedings in Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://openresearch.lsbu.ac.uk/download/42713a3017ce7b4c48741a11f5c9d88412c24e4a25ad3f57ae1cef8eb7ed9551/128249/CFGP_Springer_REVISION_28102014_Sottomesso%20e%20Accettato.pdf

zbMATH Keywords

Markov chainstransition probabilitiesbootstrapping

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Bootstrap, jackknife and other resampling methods (62F40) Markov processes: hypothesis testing (62M02)

Cites Work

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• Bootstrap methods: another look at the jackknife
• Sieve bootstrap for time series
• Relevant states and memory in Markov chain bootstrapping and simulation
• Variable length Markov chains
• Second-order properties of regeneration-based bootstrap for atomic Markov chains
• Higher-order multivariate Markov chains and their applications
• A tabu search heuristic procedure in Markov chain bootstrapping
• Tapered block bootstrap
• Separability Criterion for Density Matrices
• A MARKOVIAN LOCAL RESAMPLING SCHEME FOR NONPARAMETRIC ESTIMATORS IN TIME SERIES ANALYSIS
• Bootstrap Methods for Markov Processes

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