sarima
Simulation and Prediction with Seasonal ARIMA Models
Functions, classes and methods for time series modelling with ARIMA
and related models. The aim of the package is to provide consistent
interface for the user. For example, a single function autocorrelations()
computes various kinds of theoretical and sample autocorrelations. This is
work in progress, see the documentation and vignettes for the current
functionality. Function sarima() fits extended multiplicative seasonal
ARIMA models with trends, exogenous variables and arbitrary roots on the
unit circle, which can be fixed or estimated (for the algebraic basis for
this see
'sarima' is an R package for time series modelling.
Installing sarima
Install the latest stable version of
sarima from CRAN:
install.packages("sarima")
You can install the development version of
sarima from Github:
remotes::install_github("GeoBosh/sarima")
Overview
Functions, classes and methods for time series modelling with ARIMA and related models. The aim of the package is to provide consistent interface for the user. For example, a single function autocorrelations() computes various kinds of theoretical and sample autocorrelations. This is work in progress, see the documentation and vignettes for the current functionality. Function sarima() fits extended multiplicative seasonal ARIMA models with trends, exogenous variables and arbitrary roots on the unit circle, which can be fixed or estimated.
Reference manuals and vignettes are available as usual from running R sessions. For example, this shows the available vignettes:
vignette(package = "sarima") # which vignettes are available?
These commands open the vignettes (the names are taken from the output of the command above):
vignette("white_noise_tests", package = "sarima")
vignette("garch_tests_example", package = "sarima")
Alternatively, here are some links to online versions of the documentation:
The documentation is incomplete and some features are unfinished. Bug reports and suggestions are welcome.