Nonparametric density estimation for linear processes with infinite variance

DOI10.1007/s10463-007-0149-xzbMath1332.62123OpenAlexW2100560579MaRDI QIDQ730761

Toshio Honda

Publication date: 30 September 2009

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

Full work available at URL: http://hermes-ir.lib.hit-u.ac.jp/hermes/ir/re/16959/070econDP05-13.pdf

zbMATH Keywords

kernel density estimatordomain of attractionlinear processesstable distributionmartingale central limit theoremnoncentral limit theorem

Mathematics Subject Classification ID

Infinitely divisible distributions; stable distributions (60E07) Density estimation (62G07) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20) Central limit and other weak theorems (60F05)

Related Items

On nonparametric density estimation for multivariate linear long-memory processes ⋮ Nonparametric quantile regression with heavy-tailed and strongly dependent errors ⋮ Nonparametric regression for dependent data in the errors-in-variables problem ⋮ Nonstationarity in time series of state densities

Uses Software

• fBasics
• RMetrics

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