Functional data: local linear estimation of the conditional density and its application
By Jacques Demongeot, Ali Laksaci, Fethi Madani, Mustapha Rachdi. 2013
59 citations recorded by the source corpus.
In this paper, we introduce a new nonparametric estimation procedure of the conditional density of a scalar response variable given a random variable taking values in a semi-metric space. Under some general conditions, we establish both the pointwise and the uniform almost-complete consistencies with convergence rates of the conditional density estimator related to this estimation procedure. Moreover, we give some particular cases of our results which can also be considered as novel in the finite-dimensional setting. Notice also that the results of this paper are used to derive some asymptotic properties of the local linear estimator of the conditional mode.
Subfields: Artificial Intelligence, Statistics and Probability
View Paper: https://www.semanticscholar.org/paper/928ca0bf945d7e1b67330006f5c7f6542fb690d3
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In Artificial Intelligence
In Statistics and Probability
- Nengxiang Ling
- Philippe Vieu
- Jacques Demongeot
- Mustapha Rachdi
- Ali Laksaci
- Saâdia Rahmani
- Heng Lian
- Frédéric Ferraty
Citations in the corpus
- Nonparametric modelling for functional data: selected survey and tracks for future (2018, background): “Local linear estimates have been introduced in [105] and rates of convergence are obtained (see also [106]).”
- On the Local Linear Modelization of the Conditional Distribution for Functional Data (2014, methodology): “346 J. Demongeot et al. Acknowledgements.”