Package: ForecastTB 1.0.1
ForecastTB: Test Bench for the Comparison of Forecast Methods
Provides a test bench for the comparison of forecasting methods in uni-variate time series. Forecasting methods are compared using different error metrics. Proposed forecasting methods and alternative error metrics can be used. Detailed discussion is provided in the vignette.
Authors:
ForecastTB_1.0.1.tar.gz
ForecastTB_1.0.1.zip(r-4.5)ForecastTB_1.0.1.zip(r-4.4)ForecastTB_1.0.1.zip(r-4.3)
ForecastTB_1.0.1.tgz(r-4.4-any)ForecastTB_1.0.1.tgz(r-4.3-any)
ForecastTB_1.0.1.tar.gz(r-4.5-noble)ForecastTB_1.0.1.tar.gz(r-4.4-noble)
ForecastTB_1.0.1.tgz(r-4.4-emscripten)ForecastTB_1.0.1.tgz(r-4.3-emscripten)
ForecastTB.pdf |ForecastTB.html✨
ForecastTB/json (API)
| # Install 'ForecastTB' in R: |
| install.packages('ForecastTB', repos = c('https://neerajdhanraj.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/neerajdhanraj/forecasttb/issues
Last updated 5 years agofrom:9b7e8329c5. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 17 2024 |
| R-4.5-win | NOTE | Nov 17 2024 |
| R-4.5-linux | NOTE | Nov 17 2024 |
| R-4.4-win | NOTE | Nov 17 2024 |
| R-4.4-mac | NOTE | Nov 17 2024 |
| R-4.3-win | NOTE | Nov 17 2024 |
| R-4.3-mac | NOTE | Nov 17 2024 |
Exports:append_choose_monte_carloplot_circleprediction_errors
Dependencies:circlizecliclustercolorspacecommonmarkcpp11curldata.tabledecomposedPSFdplyrfansifarverforecastfracdiffgenericsggplot2ggtextGlobalOptionsgluegridExtragridtextgtableimputeTestbenchimputeTSisobandjpegjsonlitelabelinglatticelifecyclelmtestmagrittrmarkdownMASSMatrixmgcvmunsellnlmennetpillarpkgconfigplyrpngPSFpurrrquadprogquantmodR6RColorBrewerRcppRcppArmadilloreshape2rlangRlibeemdscalesshapestinepackstringistringrtibbletidyrtidyselecttimeDatetseriesTTRurcautf8vctrsviridisLitewithrxfunxml2xtszoo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Function to append new methods in the study | append_ |
| Function to select the desired methods in the study | choose_ |
| Function to use Monte Carlo strategy | monte_carlo |
| Function to plot comparison of Predicted values in a circular ring | plot_circle |
| Function to plot comparison of Prediction methods | plot.prediction_errors |
| Function working as testbench for comparison of Prediction methods | prediction_errors |
