Consistency of minimum description length model selection for piecewise stationary time series models

DOI10.1214/13-EJS769zbMath1337.62254OpenAlexW2013776580MaRDI QIDQ1951119

Richard A. Davis, Chun Yip Yau

Publication date: 29 May 2013

Published in: Electronic Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://projecteuclid.org/euclid.ejs/1359564355

zbMATH Keywords

GARCHnon-stationary time seriesmultiple change pointsminimum description length (MDL) principlepiecewise-stationary processes

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items (8)

Piecewise autoregression for general integer-valued time series ⋮ On consistency of minimum description length model selection for piecewise autoregressions ⋮ Detecting abrupt changes in the spectra of high-energy astrophysical sources ⋮ BOOTSTRAP INFERENCE FOR MULTIPLE CHANGE-POINTS IN TIME SERIES ⋮ Generalized threshold latent variable model ⋮ Two-stage data segmentation permitting multiscale change points, heavy tails and dependence ⋮ Segmented Model Selection in Quantile Regression Using the Minimum Description Length Principle ⋮ Multiple changepoint detection with partial information on changepoint times

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