Wavelet change‐point estimation for long memory non‐parametric random design models

Lihong Wang and Haiyan Cai

Journal of Time Series Analysis, 2010, vol. 31, issue 2, 86-97

Abstract: For a random design regression model with long memory design and long memory errors, we consider the problem of detecting a change point for sharp cusp or jump discontinuity in the regression function. Using the wavelet methods, we obtain estimators for the change point, the jump size and the regression function. The strong consistencies of these estimators are given in terms of convergence rates.

Date: 2010
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https://doi.org/10.1111/j.1467-9892.2009.00646.x

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Persistent link: https://EconPapers.repec.org/RePEc:bla:jtsera:v:31:y:2010:i:2:p:86-97

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