Nothing
#' Rsfar: A Package for Seasonal Functional Autoregressive Models.
#'
#' The Rsfar package provides the collection of necessary
#' functions for simulating, estimating and forecasting seasonal functional
#' autoregressive time series of order one.
#'
#'@details
#' Functional autoregressive models are popular for functional time series analysis, but
#' the standard formulation fails to address seasonal behavior in functional time series data.
#' To overcome this shortcoming, we introduce seasonal functional autoregressive time series
#' models. For the model of order one, we provide estimation, prediction and simulation methods.
#'
#'@seealso
#' \code{\link{sfar}}, \code{\link{predict.sfar}},
#'
#'@references
#' Atefeh Z., Hossein H., Maryam H., and R.J Hyndman (2021).
#' Seasonal functional autoregressive models. Manuscript submitted for publication.
#' \url{https://robjhyndman.com/publications/sfar/}
#'
#' @docType package
#' @name Rsfar-package
NULL
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.