Nonparametric curve estimation from contaminated data
by Dr Aurore Delaigle
Abstract: In many real life applications observations can not be measured precisely and the only data available are contaminated by measurement errors (for example, due to the inaccuracy of the measurement device used). When applied to such data, standard nonparametric estimators of a density or a regression curve are not consistent, but there exist in the literature nonparametric estimators especially adapted to the measurement errors. We introduce the problem of measurement errors, define appropriate nonparametric estimators and discuss some of their interesting properties (practical and theoretical).
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