Estimating with kernel smoothers the mean of functional data in a finite population setting. A note on variance estimation in presence of partially observed trajectories

This paper studies, in a survey sampling framework with unequal probability sampling designs, three nonparametric kernel estimators for the mean curve in presence of discretized trajectories with missing values. Their pointwise variances are approximated thanks to linearization techniques.

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Year of publication:	2015
Authors:	Cardot, Hervé ; De Moliner, Anne ; Goga, Camelia
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 99.2015, C, p. 156-166
Publisher:	Elsevier
Subject:	Functional data \| Hájek estimator \| Horvitz–Thompson estimator \| Missing values \| Nonparametric estimation \| Survey sampling

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10011208308