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Wavelet detection of change points in hazard rate models with censored dependent data

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  • Jingle Wang
  • Ming Zheng

Abstract

The detection of change points in hazard rate has been studied a lot for independently and identically distributed survival data. However, in some domains, the survival times may be dependent. This paper considers the detection and estimation of change points in hazard rate for censored dependent data. We construct a nonparametric test statistic based on the wavelet method for change point detection. We also utilise the test statistic to design estimators for the number, the locations, and the jump sizes of the change points in hazard rate. The corresponding asymptotic properties are derived. Some simulation studies are conducted to assess the finite sample performances of the proposed method.

Suggested Citation

  • Jingle Wang & Ming Zheng, 2012. "Wavelet detection of change points in hazard rate models with censored dependent data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 24(3), pages 765-781.
    • Handle: RePEc:taf:gnstxx:v:24:y:2012:i:3:p:765-781
    DOI: 10.1080/10485252.2012.700055
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    References listed on IDEAS

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    1. Guosheng Yin & Jianwen Cai, 2005. "Quantile Regression Models with Multivariate Failure Time Data," Biometrics, The International Biometric Society, vol. 61(1), pages 151-161, March.
    2. Zhou, Yong & Wan, Alan T.K. & Xie, Shangyu & Wang, Xiaojing, 2010. "Wavelet analysis of change-points in a non-parametric regression with heteroscedastic variance," Journal of Econometrics, Elsevier, vol. 159(1), pages 183-201, November.
    3. Anestis Antoniadis & Irene Gijbels & Brenda Macgibbon, 2000. "Non‐parametric Estimation for the Location of a Change‐point in an Otherwise Smooth Hazard Function under Random Censoring," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 27(3), pages 501-519, September.
    4. Taoufik Bouezmarni & Jeroen Rombouts, 2008. "Density and hazard rate estimation for censored and α-mixing data using gamma kernels," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 20(7), pages 627-643.
    5. Liang Han-Ying & Mammitzsch Volker & Steinebach Josef, 2005. "Nonlinear wavelet density and hazard rate estimation for censored data under dependent observations," Statistics & Risk Modeling, De Gruyter, vol. 23(3), pages 161-180, March.
    6. Chen, Gongmeng & Choi, Yoon K. & Zhou, Yong, 2008. "Detections of changes in return by a wavelet smoother with conditional heteroscedastic volatility," Journal of Econometrics, Elsevier, vol. 143(2), pages 227-262, April.
    7. Cai, Zongwu, 1998. "Asymptotic properties of Kaplan-Meier estimator for censored dependent data," Statistics & Probability Letters, Elsevier, vol. 37(4), pages 381-389, March.
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