Strong consistency of density estimation by orthogonal series methods for dependent variables with applications

DOI10.1007/BF02480283zbMath0445.62053OpenAlexW2012381867MaRDI QIDQ1145444

Ibrahim A. Ahmad

Publication date: 1979

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02480283

zbMATH Keywords

dependent variablesorthogonal series methodsstrong consistency of density estimation

Mathematics Subject Classification ID

Nonparametric estimation (62G05)

Related Items (7)

On the consistency and finite-sample properties of nonparametric kernel time series regression, autoregression and density estimators ⋮ Some automated methods of smoothing time-dependent data ⋮ Nonparametric estimation of the location and scale parameters based on density estimation ⋮ Integrated mean square properties of density estimation by orthogonal series methods for dependent variables ⋮ NONPARAMETRIC ESTIMATORS FOR TIME SERIES ⋮ On density estimation from ergodic processes ⋮ Kernel estimation and interpolation for time series containing missing observations

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• A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
• Probability Inequalities for Sums of Bounded Random Variables
• Estimation of Probability Density by an Orthogonal Series
• The Estimation of Probability Densities and Cumulatives by Fourier Series Methods
• Density Estimation by Orthogonal Series

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