Balanced importance resampling for Markov chains

DOI10.1016/S0378-3758(99)00088-9zbMath0942.62048MaRDI QIDQ1969150

Yanyan Li

Publication date: 24 August 2000

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

bootstraptransition probabilitiesinvariant distributionsfinite state Markov chainbalanced importance resampling

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Central limit and other weak theorems (60F05) Markov processes: estimation; hidden Markov models (62M05) Nonparametric statistical resampling methods (62G09)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Performance of balanced bootstrap resampling in distribution function and quantile problems
• Bootstrapping Markov chains: Countable case
• On the first-order Edgeworth expansion for a Markov chain
• Central limit theorems for multinomial sums
• Bootstrap methods: another look at the jackknife
• Some continuous Edgeworth expansions for Markov chains with applications to bootstrap
• Bootstrap confidence intervals. With comments and a rejoinder by the authors
• Balanced importance resampling for the bootstrap
• Importance Sampling for Stochastic Simulations
• Asymptotic bootstrap validity for finite markov chains
• Asymptotic expansions in the central limit theorem for compound and Markov processes
• Importance Sampling for Bootstrap Confidence Intervals
• Importance resampling for markov chains
• Balanced resampling for bootstrapping finite state markov chains
• Efficient Bootstrap Simulation
• Moments of Randomly Stopped Sums

This page was built for publication: Balanced importance resampling for Markov chains