Nonparametric weighted estimators for biased data

Abstract : Several adaptive methods to estimate a density from biased data are pre-sented. Risk bounds for the estimators are provided and an empirical study is performed to compare various kernel and projection estimators associated with different adaptation methods, namely Lepski-type bandwidth selection in pointwise and global settings and model selection for projection estimators. A real data example taken from fluorescence lifetime measurements is also studied.
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Fabienne Comte, Tabea Rebafka. Nonparametric weighted estimators for biased data. Journal of Statistical Planning and Inference, Elsevier, 2016, 174, pp.104-128. ⟨10.1016/j.jspi.2016.01.008⟩. ⟨hal-01101970⟩

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