README.md

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forecastSNSTSexamples

Data examples for the R package 'forecastSNSTS'

The aim of the forecastSNSTS package is to distribute the data and R code to replicate the empirical examples form Section 5 in the following paper (click to open):

Predictive, finite-sample model choice for time series under stationarity and non-stationarity (2017/06/03)

Older version of the package can be used to replicate the examples in older versions of the paper. In particular, version 1.1-0 can be used to replicate the examples in

Predictive, finite-sample model choice for time series under stationarity and non-stationarity (2016/11/15)

Replicating the examples

First, if you have not done so already, install R from http://www.r-project.org (click on download R, select a location close to you, and download R for your platform). Once you have the latest version of R installed and started execute the following commands on the R shell:

install.packages("devtools") devtools::install_github("tobiaskley/forecastSNSTSexamples")

This will first install the R package devtools and then use it to install the latest (development) version of forecastSNSTSexamples from the GitHub repository.

If you want to install an older version of the examples you can, for example, call devtools::install_github("tobiaskley/forecastSNSTSexamples", ref="v1.1-0")

Now that you have R and forecastSNSTSexamples installed you can load the package and access the help files:

library(forecastSNSTSexamples)
help("forecastSNSTSexamples")

To access the (documentation provided with the) data

library(forecastSNSTSexamples)
help("LondonHPI")
help("Hohenpeissenberg")
help("FTSE100")

Finally, to replicate the empirical examples from Section 5 in the paper call

library(forecastSNSTSexamples)
demo("LondonHPI")
demo("Hohenpeissenberg")
demo("FTSE100")


tobiaskley/forecastSNSTSexamples documentation built on May 31, 2019, 4:44 p.m.