Package: forecasteR 2.0.2
Oldemar Rodriguez
forecasteR: Time Series Forecast System
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>.
Authors:
forecasteR_2.0.2.tar.gz
forecasteR_2.0.2.zip(r-4.5)forecasteR_2.0.2.zip(r-4.4)forecasteR_2.0.2.zip(r-4.3)
forecasteR_2.0.2.tgz(r-4.4-any)forecasteR_2.0.2.tgz(r-4.3-any)
forecasteR_2.0.2.tar.gz(r-4.5-noble)forecasteR_2.0.2.tar.gz(r-4.4-noble)
forecasteR_2.0.2.tgz(r-4.4-emscripten)forecasteR_2.0.2.tgz(r-4.3-emscripten)
forecasteR.pdf |forecasteR.html✨
forecasteR/json (API)
| # Install 'forecasteR' in R: |
| install.packages('forecasteR', repos = c('https://promidat.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/promidat/forecaster/issues
Last updated 1 years agofrom:34774818c8. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 15 2024 |
| R-4.5-win | OK | Oct 15 2024 |
| R-4.5-linux | OK | Oct 15 2024 |
| R-4.4-win | OK | Oct 15 2024 |
| R-4.4-mac | OK | Oct 15 2024 |
| R-4.3-win | OK | Oct 15 2024 |
| R-4.3-mac | OK | Oct 15 2024 |
Exports:calibrar.arimacalibrar.HWdf_periodsdfnormale_acfe_decomposee_histnormale_pacfe_periodse_qqe_tcget_startgrafico.erroresMSEpred.tskerasRERMSERSSrun_appsmoothingtabla.errorestext_toDatetskerasvar.categoricasvar.numericas
Dependencies:attemptbackportsbase64encbroombslibcachemclicolorspacecolourpickercommonmarkconfigcorrplotcountrycodecpp11crayoncrosstalkcurldigestdplyrDTecharts4revaluatefansifarverfastmapfontawesomeforecastfracdifffreshfsgenericsggplot2gluegolemgtableherehighrhtmltoolshtmlwidgetshttpuvisobandjquerylibjsonlitekerasknitrlabelinglaterlatticelazyevallifecyclelmtestlubridatemagrittrMASSMatrixmemoisemgcvmimeminiUImunsellnlmennetpillarpkgconfigpngprocessxpromisespspurrrquadprogquantmodR6rappdirsRColorBrewerRcppRcppArmadilloRcppTOMLreticulaterlangrmarkdownrprojrootrstudioapisassscalesshinyshinyAceshinycustomloadershinydashboardshinydashboardPlusshinyjssourcetoolsstringistringrtensorflowtfautographtfrunstibbletidyrtidyselecttimechangetimeDatetinytextseriesTTRurcautf8vctrsviridisLitewaiterwhiskerwithrxfunxtablextsyamlzeallotzoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Best parameters arima model | calibrar.arima |
| Best parameters HoltWinters model | calibrar.HW |
| Periodogram Data.frame | df_periods |
| Data.frame with normal test | dfnormal |
| Best parameters arima model | e_acf |
| Decompose plot | e_decompose |
| Normal plot | e_histnormal |
| Best parameters arima model | e_pacf |
| Periodogram Plot | e_periods |
| Qplot + Qline | e_qq |
| Tendencia y Estacionalidad | e_tc |
| Time Series Forecast System | forecasteR |
| Get ts start of a time series | get_start |
| Error plot for all predictions | grafico.errores |
| Mean Square Error | MSE |
| Time series forecasts for a keras model. | pred.tskeras |
| Relative Error | RE |
| Root Mean Square Error | RMSE |
| RSS | RSS |
| Run the Shiny Application | run_app |
| Apply rolling to a numeric vector. | smoothing |
| Error table for all predictions | tabla.errores |
| Convert character to dates | text_toDate |
| keras model for time series. | tskeras |
| Filter category variables of a data.frame | var.categoricas |
| Filter numeric variables of a data.frame | var.numericas |