When stochastic errors are added to data from a distribution with a sharp boundary, such as a changepoint or a frontier, nonparametric estimation of the boundary can be interpreted as a problem of deconvolution. We argue that, rather than attempting to estimate the distribution of the uncorrupted data, and thereby approximate the boundary, one might focus more directly on the boundary estimation problem.
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Paper provided by Catholique de Louvain - Institut de statistique in its series Papers with number
0012.
Length: 28 pages Date of creation: 2000 Date of revision: Handle: RePEc:fth:louvis:0012
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Find related papers by JEL classification: C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Estimation C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Semiparametric and Nonparametric Methods