Strong consistency and rates for recursive nonparametric conditional probability density estimates under \((\alpha{}, \beta{})\)-mixing conditions

DOI10.1016/0304-4149(91)90097-VzbMath0747.62037OpenAlexW1970713663MaRDI QIDQ1177215

Zong-Wu Cai

Publication date: 26 June 1992

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4149(91)90097-v

zbMATH Keywords

rate of convergencestrong consistency(alpha,beta)-mixing stationary processa.s. convergence ratesbandwidths of kernel estimatesconditional probability density estimatereal-valued stationary processrecursive type kernel estimators

Mathematics Subject Classification ID

Density estimation (62G07) Non-Markovian processes: estimation (62M09) Strong limit theorems (60F15)

Related Items (5)

Hajek-Renyi-type inequality for \((\alpha, \beta)\)-mixing sequences and its application to change-point model ⋮ Consistency properties for the estimators of partially linear regression model under dependent errors ⋮ Complete moment convergence for (α,β)-mixing random variables and its application ⋮ Conditional Density Estimation in the Single Functional Index Model for α-Mixing Functional Data ⋮ Functional estimation for time series: Uniform convergence properties

Cites Work

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• Nonparametric estimation of conditional probability densities and expectations of stationary processes: Strong consistency and rates
• Multilinear forms and measures of dependence between random variables
• On the consistency and finite-sample properties of nonparametric kernel time series regression, autoregression and density estimators
• Strong consistency and rates for recursive probability density estimators of stationary processes
• Remarks on some recursive estimators of a probability density
• NONPARAMETRIC ESTIMATORS FOR TIME SERIES

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