https://github.com/cran/ftsa
Raw File
Tip revision: c3715412cc972271c2e6d9ee895aed21b6f67c41 authored by Han Lin Shang on 31 March 2011, 15:18:38 UTC
version 2.6
Tip revision: c371541
ftsa-package.Rd
\name{ftsa-package}
\alias{ftsa-package}
\docType{package}
\title{
Functional time series analysis
}
\description{
This package presents descriptive statistics for modeling functional data; implements principal component regression and partial least squares regression to provide point and distributional forecasts for functional data; utilizes ordinary least squares, penalized least squares, ridge regression, and moving block approaches to dynamically update point and distributional forecasts when partial data points in the most recent curve are observed.
}
\author{
Rob J Hyndman and Han Lin Shang 

Maintainer: Han Lin Shang <HanLin.Shang@buseco.monash.edu.au>
}
\references{
R. J. Hyndman and H. L. Shang. (2010) "Rainbow plots, bagplots, and boxplots for functional data", \emph{Journal of Computational and Graphical Statistics}, \bold{19}(1), 29-45.

R. J. Hyndman and H. L. Shang (2009) "Forecasting functional time series (with discussion)", \emph{Journal of the Korean Statistical Society}, \bold{38}(3), 199-221.

H. L. Shang and R. J. Hyndman (2009) "Nonparametric time series forecasting with dynamic updating", In R. S. Anderssen, R. D. Braddock and L.T.H. Newham (eds), 18th World IMACS Congress and MODSIM09 International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand and International Association for Mathematics and Computers in Simulation, July 2009, pp. 1552-1558. ISBN: 978-0-9758400-7-8. 
\url{http://www.mssanz.org.au/modsim09/D11/shang.pdf}
}
\keyword{package}


back to top