tsfknn: Time Series Forecasting Using Nearest Neighbors

Allows to forecast time series using nearest neighbors regression Francisco Martinez, Maria P. Frias, Maria D. Perez-Godoy and Antonio J. Rivera (2019) <doi:10.1007/s10462-017-9593-z>. When the forecasting horizon is higher than 1, two multi-step ahead forecasting strategies can be used. The model built is autoregressive, that is, it is only based on the observations of the time series. The nearest neighbors used in a prediction can be consulted and plotted.

Version: 0.5.2
Depends: R (≥ 3.6.0)
Imports: ggplot2 (≥ 3.1.1), graphics, Rcpp, stats, utils
LinkingTo: Rcpp
Suggests: knitr, rmarkdown, testthat (≥ 2.0.1)
Published: 2023-09-04
Author: Francisco Martinez [aut, cre]
Maintainer: Francisco Martinez <fmartin at ujaen.es>
BugReports: https://github.com/franciscomartinezdelrio/tsfknn/issues
License: GPL-2
URL: https://github.com/franciscomartinezdelrio/tsfknn
NeedsCompilation: yes
Citation: tsfknn citation info
Materials: README NEWS
In views: TimeSeries
CRAN checks: tsfknn results


Reference manual: tsfknn.pdf
Vignettes: Time Series Forecasting with KNN in R: the tsfknn Package


Package source: tsfknn_0.5.2.tar.gz
Windows binaries: r-devel: tsfknn_0.5.2.zip, r-release: tsfknn_0.5.2.zip, r-oldrel: tsfknn_0.5.2.zip
macOS binaries: r-release (arm64): tsfknn_0.5.2.tgz, r-oldrel (arm64): tsfknn_0.5.2.tgz, r-release (x86_64): tsfknn_0.5.2.tgz, r-oldrel (x86_64): tsfknn_0.5.2.tgz
Old sources: tsfknn archive


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