Testing for change points in time series models and limiting theorems for NED sequences
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Publication:2642747
DOI10.1214/009053606000001514zbMath1194.62017arXiv0708.2369OpenAlexW3104524372MaRDI QIDQ2642747
Publication date: 4 September 2007
Published in: The Annals of Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/0708.2369
Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Strong limit theorems (60F15) Functional limit theorems; invariance principles (60F17) Asymptotic properties of parametric tests (62F05)
Related Items (21)
LOCAL LINEAR FITTING UNDER NEAR EPOCH DEPENDENCE: UNIFORM CONSISTENCY WITH CONVERGENCE RATES ⋮ On consistency of minimum description length model selection for piecewise autoregressions ⋮ Consistent order selection for ARFIMA processes ⋮ A Randomized Sequential Procedure to Determine the Number of Factors ⋮ Likelihood ratio tests for the structural change of an AR(p) model to a Threshold AR(p) model ⋮ Moment bounds and mean squared prediction errors of long-memory time series ⋮ Asymptotically distribution free test for parameter change in a diffusion process model ⋮ Structural changes in autoregressive models for binary time series ⋮ Testing for changes in linear models using weighted residuals ⋮ Robust Wilcoxon‐Type Estimation of Change‐Point Location Under Short‐Range Dependence ⋮ Testing for structural stability in the whole sample ⋮ Constancy test for FARIMA long memory processes ⋮ Fourier Methods for Sequential Change Point Analysis in Autoregressive Models ⋮ Test for parameter change in ARMA models with GARCH innovations ⋮ Non‐Parametric Change‐Point Tests for Long‐Range Dependent Data ⋮ Segmenting mean-nonstationary time series via trending regressions ⋮ ESTIMATION OF CHANGE-POINTS IN LINEAR AND NONLINEAR TIME SERIES MODELS ⋮ Optimal change-point estimation in time series ⋮ Estimating a change point in the long memory parameter ⋮ Testing for structural change of AR model to threshold AR model ⋮ Comments on: ``Extensions of some classical methods in change point analysis
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