localFDA: Localization Processes for Functional Data Analysis

Implementation of a theoretically supported alternative to k-nearest neighbors for functional data to solve problems of estimating unobserved segments of a partially observed functional data sample, functional classification and outlier detection. The approximating neighbor curves are piecewise functions built from a functional sample. Instead of a distance on a function space we use a locally defined distance function that satisfies stabilization criteria. The package allows the implementation of the methodology and the replication of the results in Elías, A., Jiménez, R. and Yukich, J. (2020) <arXiv:2007.16059>.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: stats, graphics
Published: 2020-09-30
Author: Antonio Elías [aut, cre], Raul Jiménez [aut], Joe Yukich [aut]
Maintainer: Antonio Elías <antonioefz91 at gmail.com>
BugReports: https://github.com/aefdz/localFDA
License: GPL-3
URL: https://github.com/aefdz/localFDA
NeedsCompilation: no
CRAN checks: localFDA results


Reference manual: localFDA.pdf
Package source: localFDA_1.0.0.tar.gz
Windows binaries: r-devel: localFDA_1.0.0.zip, r-release: localFDA_1.0.0.zip, r-oldrel: localFDA_1.0.0.zip
macOS binaries: r-release: localFDA_1.0.0.tgz, r-oldrel: localFDA_1.0.0.tgz


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