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 (2017) <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: 0.2.0
Depends: R (≥ 3.5.0)
Imports: ggplot2 (≥ 3.1.1), graphics, stats, utils
Suggests: knitr, rmarkdown, testthat (≥ 2.0.1)
Published: 2019-04-09
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: no
Materials: README NEWS
In views: TimeSeries
CRAN checks: tsfknn results

Downloads:

Reference manual: tsfknn.pdf
Vignettes: Time Series Forecasting with KNN in R: the tsfknn Package
Package source: tsfknn_0.2.0.tar.gz
Windows binaries: r-devel: tsfknn_0.2.0.zip, r-release: tsfknn_0.2.0.zip, r-oldrel: tsfknn_0.2.0.zip
OS X binaries: r-release: tsfknn_0.2.0.tgz, r-oldrel: tsfknn_0.2.0.tgz
Old sources: tsfknn archive

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