Improved estimators for constrained Markov chain models

DOI10.1016/S0167-7152(01)00121-3zbMath1002.62065WikidataQ127493954 ScholiaQ127493954MaRDI QIDQ5953886

Ursula U. Müller, Anton Schick, Wolfgang Wefelmeyer

Publication date: 13 January 2003

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

zbMATH Keywords

influence functionasymptotically linear estimatorempirical estimatorlinear autoregressionregular estimatorreversible chainsymmetric chain

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Nonparametric estimation (62G05) Markov processes: estimation; hidden Markov models (62M05)

Related Items (6)

Estimating invariant laws of linear processes by \(U\)-statistics. ⋮ Root n consistent and optimal density estimators for moving average processes ⋮ Efficient prediction for linear and nonlinear autoregressive models ⋮ Testing lumpability in Markov chains. ⋮ Regeneration-based statistics for Harris recurrent Markov chains ⋮ Bootstrapping Robust Statistics for Markovian Data Applications to Regenerative R‐Statistics and L‐Statistics

Cites Work

• Markov chains and stochastic stability
• Efficient estimation of the stationary distribution for exponentially ergodic Markov chains
• Adjustment by minimum discriminant information
• Reversible Markov chains and optimality of symmetrized empirical estimators
• Estimating joint distributions of Markov chains
• Estimating invariant laws of linear processes by \(U\)-statistics.
• Efficiency of empirical estimators for Markov chains
• Prediction in invertible linear processes
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