Median regression from twice censored data

Research output: Contribution to journalArticlepeer-review

Abstract

An adjusted least absolute deviation estimating function, founded on the inverse (probability of) censoring weighted approach, is proposed. Covariate-free left and right censoring is assumed. When left censoring is absent, the proposed estimating function reduces to its right-censored counterpart. Consistency and asymptotic normality of the estimator of the regression parameter are derived. Finite sample performance is investigated via simulations. Application of the proposed method is illustrated using some synthetic data sets.

Original languageEnglish (US)
Article number108955
JournalStatistics and Probability Letters
Volume168
DOIs
StatePublished - Jan 2021

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Keywords

  • Curse of dimensionality
  • Empirical likelihood
  • Local linearity
  • Measure preserving transformation
  • Minimum dispersion statistic
  • Subset inference

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