Estimating the endpoint of a distribution in the presence of additive observation errors
We consider the problem of estimating the endpoint of a probability distribution in the presence of observation errors, when the available sample is drawn from the convolution with some error density. We study the cases of Gaussian errors and errors with bounded support, and propose estimators that are optimal in a minimax sense.
Volume (Year): 68 (2004)
Issue (Month): 1 (June)
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References listed on IDEAS
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- Kneip, Alois & Park, Byeong U. & Simar, L opold, 1998. "A Note On The Convergence Of Nonparametric Dea Estimators For Production Efficiency Scores," Econometric Theory, Cambridge University Press, vol. 14(06), pages 783-793, December.
- Hall P. & Simar L., 2002.
"Estimating a Changepoint, Boundary, or Frontier in the Presence of Observation Error,"
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American Statistical Association, vol. 97, pages 523-534, June.
- Hall, P. & Simar, L., 2000. "Estimating a Changepoint, Boundary of Frontier in the Presence of Observation Error," Papers 0012, Catholique de Louvain - Institut de statistique.
- Hall, Peter & Nussbaum, Michael & Stern, Steven E., 1997. "On the Estimation of a Support Curve of Indeterminate Sharpness," Journal of Multivariate Analysis, Elsevier, vol. 62(2), pages 204-232, August.
- Hardle, W. & Park, B. U. & Tsybakov, A. B., 1995. "Estimation of Non-sharp Support Boundaries," Journal of Multivariate Analysis, Elsevier, vol. 55(2), pages 205-218, November. Full references (including those not matched with items on IDEAS)
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