Deconvolution of P (X < Y) with supersmooth error distributions

Research output: Contribution to journalArticlepeer-review


This paper deals with the nonparametric estimation of P (X < Y) when both X and Y are observed with additional errors. We develop a deconvolution estimator and show that it is minimax optimal and adaptive in the case of supersmooth error distributions. Some numerical results are presented.

Original languageEnglish
Pages (from-to)1880-1887
Number of pages8
JournalStatistics and Probability Letters
Issue number8
StatePublished - Aug 2013
Externally publishedYes


  • Adaptive estimator
  • Deconvolution
  • Measurement error
  • Receiver operating characteristic
  • Stress-strength model

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty


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