Title: Forecasting for Stationary and Non-Stationary Time Series
Authors@R: c(person("Tobias", "Kley", email = "t.kley@lse.ac.uk", role = c("aut", "cre")),
person("Philip", "Preuss", email = "philip.preuss@rub.de", role = c("aut")),
person("Piotr", "Fryzlewicz", email = "p.fryzlewicz@lse.ac.uk", role = c("aut")))
Description: Methods to compute linear h-step prediction coefficients based
on localised and iterated Yule-Walker estimates and empirical mean square
prediction errors for the resulting predictors.
Collate: 'RcppExports.R' 'forecastSNSTS-package.R' 'models.R' 'mspe.R'

Description: Methods to compute linear h-step ahead prediction coefficients based
on localised and iterated Yule-Walker estimates and empirical mean squared
prediction errors for the resulting predictors. Also, functions to compute
autocovariances for AR(p) processes, to simulate tvARMA(p,q) time series,
and to verify an assumption from a paper by the authors.
Collate: 'RcppExports.R' 'acfARp.R' 'f.R' 'forecastSNSTS-package.R'

and to verify an assumption from Kley et al. (2017),

and absolute prediction errors for the resulting predictors. Also, functions
to compute autocovariances for AR(p) processes, to simulate tvARMA(p,q) time
series, and to verify an assumption from Kley et al. (2017),

Authors@R: c(person("Tobias", "Kley", email = "tobias.kley@bristol.ac.uk", role = c("aut", "cre")),
series, and to verify an assumption from Kley et al. (2019), Electronic of Statistics,

person(given = "Diego", family = "Jiménez", role = "aut"))
Description: A web application for displaying, analysing and forecasting univariate time series. Includes basic methods such as mean, naïve, seasonal naïve and drift, as well as more complex methods such as Holt-Winters Box,G and Jenkins, G (1976) <doi:10.1111/jtsa.12194> and ARIMA Brockwell, P.J. and R.A.Davis (1991) <doi:10.1007/978-1-4419-0320-4>.
Imports: DT, golem, config, forecast, htmltools, lubridate, stringr,
scales, rlang, shinyjs, shinyAce, echarts4r, htmlwidgets,
colourpicker, shinydashboard, shiny (>= 1.7.1),