Density estimation for time series by histograms

DOI10.1016/0378-3758(94)90142-2zbMath0815.62023OpenAlexW1973151042MaRDI QIDQ1330219

Lanh Tat Tran

Publication date: 29 June 1995

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0378-3758(94)90142-2

zbMATH Keywords

strong mixingdensity estimationabsolute regularityuniform strong consistencydensity of time serieshistogram estimatesintegrated mean square errorsuniform optimal rate of convergence

Mathematics Subject Classification ID

Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Related Items (15)

Consistency of the simple mode of a density for spatial processes ⋮ NONPARAMETRIC TESTS FOR SERIAL DEPENDENCE ⋮ Frequency polygons for weakly dependent processes ⋮ Nonparametric kernel regression estimation for functional stationary ergodic data: Asymptotic properties ⋮ Strong convergence of sums of \(\alpha \)-mixing random variables with applications to density estimation ⋮ Frequency polygon estimation of density function for dependent samples ⋮ Consistency of the frequency polygon estimators of density mode for strongly mixing processes ⋮ Frequency polygons for continuous random fields ⋮ Estimating beta-mixing coefficients via histograms ⋮ Testing higher and infinite degrees of stochastic dominance for small samples: a Bayesian approach ⋮ Uniform strong consistency of histogram density estimation for dependent process ⋮ Smooth quantile estimators under strong mixing: necessary and sufficient conditions on bandwidth for weak convergence ⋮ Generalised kernel smoothing for non-negative stationary ergodic processes ⋮ Strong approximation of density estimators from weakly dependent observations by density estimators from independent observations ⋮ UNIFORM CONVERGENCE RATES FOR KERNEL ESTIMATION WITH DEPENDENT DATA

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