forecastsuite: Multi-Model Time Series Forecasting Toolkit and Local App
Fits, compares and visualizes univariate time series forecasts
through an extensible model registry built largely on the 'forecast'
package: AutoRegressive Integrated Moving Average (ARIMA) and Seasonal
ARIMA (SARIMA) models (Hyndman and Khandakar (2008)
<doi:10.18637/jss.v027.i03>), Error, Trend, Seasonal (ETS) exponential
smoothing (Hyndman et al. (2002) <doi:10.1016/S0169-2070(01)00110-8>),
Trigonometric seasonality, Box-Cox transformation, AutoRegressive Moving
Average (ARMA) errors, Trend and Seasonal components (TBATS) models
(De Livera, Hyndman and Snyder (2011) <doi:10.1198/jasa.2011.tm09771>),
Neural Network AutoRegression (NNETAR) and Holt-Winters exponential
smoothing (Winters (1960) <doi:10.1287/mnsc.6.3.324>), plus optional
'Prophet' models via the 'prophet' package (Taylor and Letham (2018)
<doi:10.1080/00031305.2017.1380080>) and Long Short-Term Memory (LSTM)
networks via the 'torch' package (Hochreiter and Schmidhuber (1997)
<doi:10.1162/neco.1997.9.8.1735>). Also provides grouped series with
bottom-up and top-down reconciliation, rolling-origin cross-validation,
ensembles and residual diagnostics, following Hyndman and Athanasopoulos
(2021) <https://otexts.com/fpp3/>, and a bundled local 'shiny'
application exposing every model.
| Version: |
1.0.2 |
| Depends: |
R (≥ 4.1) |
| Imports: |
shiny, dplyr, lubridate, tibble, tidyr, stringr, plotly, DT, forecast, zoo, shinycssloaders, shinyjs, colourpicker, stats, utils, grDevices, graphics |
| Suggests: |
prophet, torch, readxl, writexl, testthat (≥ 3.0.0), withr, rmarkdown, knitr |
| Published: |
2026-10-18 |
| DOI: |
10.32614/CRAN.package.forecastsuite (may not be active yet) |
| Author: |
Mukul Maheshwari 
[aut, cre, cph] |
| Maintainer: |
Mukul Maheshwari <ryan00700 at gmail.com> |
| BugReports: |
https://github.com/SpaRroW410/Forecast_dashboard/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/SpaRroW410/Forecast_dashboard/tree/main/forecastsuite |
| NeedsCompilation: |
no |
| Materials: |
README |
| CRAN checks: |
forecastsuite results |
Documentation:
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