Jump detection in time series nonparametric regression models: a polynomial spline approach

DOI10.1007/S10463-013-0411-3zbMath1334.62071OpenAlexW1997330591MaRDI QIDQ743999

Yujiao Yang, Qiongxia Song

Publication date: 2 October 2014

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

Full work available at URL: https://doi.org/10.1007/s10463-013-0411-3

zbMATH Keywords

time seriesB-splinesnonparametric regressiondiscontinuitiesjump detection\(\alpha\)-mixing process

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Nonparametric regression and quantile regression (62G08) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to environmental and related topics (62P12) Non-Markovian processes: estimation (62M09) Non-Markovian processes: hypothesis testing (62M07)

Related Items (5)

On change-points tests based on two-samples \(U\)-statistics for weakly dependent observations ⋮ Adaptive semiparametric estimation for single index models with jumps ⋮ Jump-detection and curve estimation methods for discontinuous regression functions based on the piecewise B-spline function ⋮ Curve fitting and jump detection on nonparametric regression with missing data ⋮ Semiparametric jump-preserving estimation for single-index models

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