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.
- Adaptive estimator
- Measurement error
- Receiver operating characteristic
- Stress-strength model
ASJC Scopus subject areas
- Statistics and Probability
- Statistics, Probability and Uncertainty