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Empirical likelihood and estimation in varying coefficient models with right censored data

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  • Liugen Xue

    (Henan University)

Abstract

In this paper, the empirical likelihood and estimations problems in varying coefficient models with right censored data are investigated by using a bias correction method. Naive and residual-adjusted empirical likelihood ratios and estimators of the coefficient functions are constructed, their asymptotic distributions are obtained, and a consistent estimator of the asymptotic variance is given. The obtained results can be directly used to construct the confidence regions of the coefficient functions. Furthermore, a new method for constructing pointwise confidence intervals and simultaneous confidence bands for each coefficient function is also proposed. The proposed method is to directly calibrate the empirical log-likelihood ratio so that the obtained ratio is asymptotically chi-squared. Undersmoothing of each coefficient function is avoided, and existing data-driven methods can also effectively select the optimal bandwidth. Simulation study is performed to compare the empirical likelihood with the normal approximation-based method. An example of real data is used to illustrate our approach.

Suggested Citation

  • Liugen Xue, 2024. "Empirical likelihood and estimation in varying coefficient models with right censored data," Computational Statistics, Springer, vol. 39(3), pages 1683-1707, May.
    • Handle: RePEc:spr:compst:v:39:y:2024:i:3:d:10.1007_s00180-023-01372-2
    DOI: 10.1007/s00180-023-01372-2
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    References listed on IDEAS

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