Result: Statistical inquiry for Markov chains by bootstrap method

Title:
Statistical inquiry for Markov chains by bootstrap method
Authors:
Fuh, C. D.
Publisher Information:
Academia Sinica, Institute of Statistical Science, Taipei
Subject Terms:
Parametric tolerance and confidence regions, Asymptotic distribution theory in statistics, Markov processes: estimation, hidden Markov models, bootstrap algorithms, ergodic Markov chain, approximate confidence intervals, hitting time, transition probability, stationary distribution
Document Type:
Academic journal Article
File Description:
application/xml
Access URL:
https://zbmath.org/774826
Accession Number:
edsair.c2b0b933574d..4a868e5476dd3a956f03eed822679e65
Database:
OpenAIRE

Further Information

Summary: We propose several different bootstrap algorithms, to get approximate confidence intervals for the parameters of an ergodic Markov chain, each of which can have \(k\) possible outcomes. Small-sample comparisons are used to select the best intervals for different parameters. An illustrative example which analyzes a farmers' tenure behavior pattern data set of Taiwan is given.