Package: ahead 0.13.0
T. Moudiki
ahead: Time Series Forecasting with uncertainty quantification
Univariate and multivariate time series forecasting with uncertainty quantification.
Authors:
ahead_0.13.0.tar.gz
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ahead.pdf |ahead.html✨
ahead/json (API)
NEWS
| # Install 'ahead' in R: |
| install.packages('ahead', repos = c('https://techtonique.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/techtonique/ahead/issues
forecastingmachine-learningpredictive-modelingstatistical-learningtime-seriestime-series-forecastinguncertainty-quantification
Last updated 1 months agofrom:9a117aa57e. Checks:OK: 1 WARNING: 8. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 16 2024 |
| R-4.5-win-x86_64 | WARNING | Oct 16 2024 |
| R-4.5-linux-x86_64 | WARNING | Oct 16 2024 |
| R-4.4-win-x86_64 | WARNING | Oct 16 2024 |
| R-4.4-mac-x86_64 | WARNING | Oct 16 2024 |
| R-4.4-mac-aarch64 | WARNING | Oct 16 2024 |
| R-4.3-win-x86_64 | WARNING | Oct 16 2024 |
| R-4.3-mac-x86_64 | WARNING | Oct 16 2024 |
| R-4.3-mac-aarch64 | WARNING | Oct 16 2024 |
Exports:armagarchfbasicfcreatetrendseasondynrmfeatffitforecastgetreturnsgetsimulationsloessfloocvridge2fremovenasridgeridge2fvarf
Fit and forecast for benchmarking purposes
Rendered fromfitforecastbench.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2024-03-25
Started: 2024-03-25
Introduction to R package ahead
Rendered fromahead-vignette.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2024-03-10
Started: 2021-10-14
Plotting functions
Rendered fromahead-plotting-functions.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2023-09-15
Started: 2023-08-23
Prediction intervals for Loess forecasting (simulation-based)
Rendered fromahead-loess-forecasting.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2023-08-28
Started: 2023-08-12
Prediction intervals for multivariate time series (simulation-based)
Rendered fromahead-ridge2-prediction-intervals.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2023-09-03
Started: 2023-08-12
Risk-neutralize simulations
Rendered fromahead-neutralize.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2023-09-15
Started: 2023-09-03
Univariate forecasting with ridge2f in ahead
Rendered fromahead-univariate-season.Rmdusingknitr::rmarkdownon Oct 16 2024.Last update: 2024-03-10
Started: 2024-01-20
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| ARMA(1, 1)-GARCH(1, 1) forecasting (with simulation) | armagarchf |
| Basic forecasting (mean, median, random walk) | basicf |
| Create trend and seasonality features for univariate time series | createtrendseason |
| Dynamic regression model | dynrmf |
| Combined ets-arima-theta forecasts | eatf |
| Fit and forecast for benchmarking purposes | fitforecast |
| Calculate returns or log-returns for multivariate time series | getreturns |
| Obtain simulations (when relevant) from a selected time series | getsimulations |
| Loess forecasting | loessf |
| LOOCV for Ridge2 model | loocvridge2f |
| Plot multivariate time series forecast or residuals | plot.mtsforecast |
| Ridge2 model | ridge2f |
| Vector Autoregressive model (adapted from vars::VAR) | varf |
