Package: iForecast 1.0.9

Ho Tsung-wu

iForecast: Machine Learning Time Series Forecasting

Compute static, onestep and multistep time series forecasts for machine learning models.

Authors:Ho Tsung-wu [aut, cre]

iForecast_1.0.9.tar.gz
iForecast_1.0.9.tar.gz(r-4.5-noble)iForecast_1.0.9.tar.gz(r-4.4-noble)
iForecast_1.0.9.tgz(r-4.4-emscripten)iForecast_1.0.9.tgz(r-4.3-emscripten)
iForecast.pdf |iForecast.html✨
iForecast/json (API)

# Install 'iForecast' in R:
install.packages('iForecast', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • ES_15m - Economic and Financial Data Sets
  • ES_Daily - Economic and Financial Data Sets
  • bc - Economic and Financial Data Sets
  • macrodata - Economic and Financial Data Sets

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.30 score 1 scripts 741 downloads 7 exports 75 dependencies

Last updated 2 months agofrom:d3cb0bb497. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 01 2024
R-4.5-linuxOKDec 01 2024

Exports:iForecastrollingWindowstts.autoMLtts.caretttsAutoMLttsCaretttsLSTM

Dependencies:caretclasscliclockcodetoolscolorspacecpp11data.tablediagramdigestdplyre1071fansifarverforeachfuturefuture.applygenericsggplot2globalsgluegowergtablehardhatipredisobanditeratorsKernSmoothlabelinglatticelavalifecyclelistenvlubridatemagrittrMASSMatrixmgcvModelMetricsmunsellnlmennetnumDerivparallellypillarpkgconfigplyrpROCprodlimprogressrproxypurrrR6RColorBrewerRcpprecipesreshape2rlangrpartscalesshapeSQUAREMstringistringrsurvivaltibbletidyrtidyselecttimechangetimeDatetzdbutf8vctrsviridisLitewithr