Wavelet Change-Point Estimation for Long Memory Non-Parametric Random Design Models

Lihong Wang, Haiyan Cai, Wang Lihong

Research output: Contribution to journalArticlepeer-review

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.
Original languageAmerican English
JournalJournal of Time Series Analysis
Volume31
DOIs
StatePublished - Jan 3 2010

Disciplines

  • Econometrics
  • Mathematics
  • Applied Mathematics
  • Statistics and Probability

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