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) . When the forecasting horizon multi-step ahead forecasting strategies can be used. The model built is is higher than 1, two 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.


The goal of tsfknn is to forecast time series using KNN regression

Installation

You can install tsfknn from from github with:

# install.packages("devtools")
devtools::install_github("franciscomartinezdelrio/tsfknn")

Example

This is a basic example which shows you how to forecast with tsfknn:

library(tsfknn)
pred <- knn_forecasting(USAccDeaths, h = 12, k = 3)
pred$prediction # To see a time series with the forecasts
plot(pred) # To see a plot with the forecast
library(ggplot2)
autoplot(pred, highlight = "neighbors")  # To see the nearest neighbors

News

Reference manual

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install.packages("tsfknn")

0.1.0 by Francisco Martinez, a year ago


https://github.com/franciscomartinezdelrio/tsfknn


Report a bug at https://github.com/franciscomartinezdelrio/tsfknn/issues


Browse source code at https://github.com/cran/tsfknn


Authors: Francisco Martinez [aut, cre]


Documentation:   PDF Manual  


Task views: Time Series Analysis


GPL-2 license


Imports ggplot2, graphics, stats, utils

Suggests knitr, rmarkdown, testthat


See at CRAN