OnL1-consistency of kernel-type density estimator for stationary markov processes

DOI10.1080/03610929508831508zbMath0825.62301OpenAlexW2093996211MaRDI QIDQ4843877

B. L. S. Prakasa Rao, Mahendra Nath Mishra

Publication date: 17 August 1995

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610929508831508

zbMATH Keywords

recursive estimationstationary Markov process\(G_ 2\)-condition\(L_ 1\)-consistency

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

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• Note on the uniform convergence of density estimates for mixing random variables
• Nonparametric density and regression estimation for Markov sequences without mixing assumptions
• Asymptotic normality of some kernel-type estimators of probability density
• Density estimation for Markov processes using delta-sequences
• A note on moment bounds for strong mixing sequences
• Density estimation in a continuous-time stationary Markov process
• Kernel density estimation under dependence
• Efficiency of a Kernel Density Estimator Under an Autoregressive Dependence Model
• Nonparametric recursive estimation in stationary markov processes
• The L/sub 1/ and L/sub 2/ strong consistency of recursive kernel density estimation from dependent samples
• Recursive density estimation under dependence

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