On the cusum of squares test for variance change in nonstationary and nonparametric time series models

DOI10.1007/BF02517801zbMath1049.62051OpenAlexW2006360299MaRDI QIDQ1881411

Sangyeol Lee, Okyoung Na, Seongryong Na

Publication date: 5 October 2004

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

Full work available at URL: https://doi.org/10.1007/bf02517801

zbMATH Keywords

weak convergenceBrownian bridgestrong mixing processvariance changeautoregressive model with units rootsCusum of squares test

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

A maximum entropy type test of fit: composite hypothesis case, Recent progress in parameter change test for integer-valued time series models, MOSUM monitoring for variance change in nonparametric regression models, Modified procedures for change point monitoring in linear models, Maximum Entropy Test for Autoregressive Models, The use of temporally aggregated data in modeling and testing a variance change in a time series, A GENERAL CLASS OF CUSUM STATISTICS, A divergence test for autoregressive time series models, Monitoring Variance Change in Infinite Order Moving Average Processes and Nonstationary Autoregressive Processes, Randomised pseudolikelihood ratio change point estimator in GARCH models, Bootstrap procedures for variance breaks test in time series with a changing trend, Ratio tests for variance change in nonparametric regression, ASYMPTOTIC BEHAVIOR OF THE CUSUM OF SQUARES TEST UNDER STOCHASTIC AND DETERMINISTIC TIME TRENDS, Moving estimates test with time varying bandwidth, Modified tests for change points in variance in the possible presence of mean breaks, Sequential Monitoring Variance Changes in Location Model, CUMULATED SUM OF SQUARES STATISTICS FOR NONLINEAR AND NONSTATIONARY REGRESSIONS, Time-varying parameter auto-regressive models for autocovariance nonstationary time series

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