Package: tsforecast
Type: Package
Title: Time Series Forecasting Functions
Version: 1.3.0
Date: 2026-01-15
Authors@R: c(
    person(
      "Ka Yui Karl", "Wu",
      email = "karlwuky@suss.edu.sg",
      role = c("aut", "cre")
    )
  )
Maintainer: Ka Yui Karl Wu <karlwuky@suss.edu.sg>
Language: en-GB
Description: Fundamental time series forecasting models such as autoregressive integrated moving average (ARIMA), exponential smoothing, and simple moving average are included. For ARIMA models, the output follows the traditional parameterisation by Box and Jenkins (1970, ISBN: 0816210942, 9780816210947). Furthermore, there are functions for detailed time series exploration and decomposition, respectively. All data and result visualisations are generated by 'ggplot2' instead of conventional R graphical output. For more details regarding the theoretical background of the models see Hyndman, R.J. and Athanasopoulos, G. (2021) <https://otexts.com/fpp3/>.
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Depends: R (>= 3.5.0)
Imports: ggplot2, lubridate, forecast, tseries, scales
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2026-01-21 08:51:48 UTC; kykar
Author: Ka Yui Karl Wu [aut, cre]
Repository: CRAN
Date/Publication: 2026-01-21 12:40:02 UTC
Built: R 4.6.0; ; 2026-04-26 15:39:16 UTC; unix
