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Empirical Likelihood Confidence Intervals For Dependent Duration Data

Author

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  • El Ghouch, Anouar
  • Van Keilegom, Ingrid
  • McKeague, Ian W.

Abstract

Three types of confidence intervals are developed for a general class of functionals of a survival distribution based on censored dependent data. The confidence intervals are constructed via asymptotic normality (Wald’s method), the empirical likelihood (EL) method, and the blockwise EL method in which sample means over blocks of observations are used in place of the original data. Asymptotic results are derived to accurately calibrate the various procedures, and their performance is evaluated in a simulation study. The problem of the choice of the block size is also discussed.

Suggested Citation

  • El Ghouch, Anouar & Van Keilegom, Ingrid & McKeague, Ian W., 2011. "Empirical Likelihood Confidence Intervals For Dependent Duration Data," Econometric Theory, Cambridge University Press, vol. 27(1), pages 178-198, February.
    • Handle: RePEc:cup:etheor:v:27:y:2011:i:01:p:178-198_00
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    Cited by:

    1. Arvanitis, Stelios & Post, Thierry & Potì, Valerio & Karabati, Selcuk, 2021. "Nonparametric tests for Optimal Predictive Ability," International Journal of Forecasting, Elsevier, vol. 37(2), pages 881-898.
    2. Stelios Arvanitis & Thierry Post, 2024. "Stochastic Arbitrage Opportunities: Set Estimation and Statistical Testing," Mathematics, MDPI, vol. 12(4), pages 1-19, February.
    3. Yinxiao Huang & Stanislav Volgushev & Xiaofeng Shao, 2015. "On Self-Normalization For Censored Dependent Data," Journal of Time Series Analysis, Wiley Blackwell, vol. 36(1), pages 109-124, January.
    4. Sun, Jiajing & Hong, Yongmiao & Linton, Oliver & Zhao, Xiaolu, 2022. "Adjusted-range self-normalized confidence interval construction for censored dependent data," Economics Letters, Elsevier, vol. 220(C).

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