Package: tsfgrnn 1.0.5
tsfgrnn: Time Series Forecasting Using GRNN
A general regression neural network (GRNN) is a variant of a Radial Basis Function Network characterized by a fast single-pass learning. 'tsfgrnn' allows you to forecast time series using a GRNN model Francisco Martinez et al. (2019) <doi:10.1007/978-3-030-20521-8_17> and Francisco Martinez et al. (2022) <doi:10.1016/j.neucom.2021.12.028>. When the forecasting horizon is higher than 1, two multi-step ahead forecasting strategies can be used. The model built is autoregressive, that is, it is only based on the observations of the time series. You can consult and plot how the prediction was done. It is also possible to assess the forecasting accuracy of the model using rolling origin evaluation.
Authors:
tsfgrnn_1.0.5.tar.gz
tsfgrnn_1.0.5.zip(r-4.5)tsfgrnn_1.0.5.zip(r-4.4)tsfgrnn_1.0.5.zip(r-4.3)
tsfgrnn_1.0.5.tgz(r-4.4-x86_64)tsfgrnn_1.0.5.tgz(r-4.4-arm64)tsfgrnn_1.0.5.tgz(r-4.3-x86_64)tsfgrnn_1.0.5.tgz(r-4.3-arm64)
tsfgrnn_1.0.5.tar.gz(r-4.5-noble)tsfgrnn_1.0.5.tar.gz(r-4.4-noble)
tsfgrnn_1.0.5.tgz(r-4.4-emscripten)tsfgrnn_1.0.5.tgz(r-4.3-emscripten)
tsfgrnn.pdf |tsfgrnn.html✨
tsfgrnn/json (API)
NEWS
# Install 'tsfgrnn' in R: |
install.packages('tsfgrnn', repos = c('https://franciscomartinezdelrio.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/franciscomartinezdelrio/tsfgrnn/issues
Last updated 9 months agofrom:3dea6b4fa4. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Oct 12 2024 |
R-4.5-win-x86_64 | OK | Oct 12 2024 |
R-4.5-linux-x86_64 | OK | Oct 12 2024 |
R-4.4-win-x86_64 | OK | Oct 12 2024 |
R-4.4-mac-x86_64 | OK | Oct 12 2024 |
R-4.4-mac-aarch64 | OK | Oct 12 2024 |
R-4.3-win-x86_64 | OK | Oct 12 2024 |
R-4.3-mac-x86_64 | OK | Oct 12 2024 |
R-4.3-mac-aarch64 | OK | Oct 12 2024 |
Exports:grnn_examplesgrnn_forecastinggrnn_weightsplot_examplerolling_origin
Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6RColorBrewerRcpprlangscalestibbleutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Create a ggplot object from a grnnForecast object | autoplot.grnnForecast |
Examples of a GRNN model | grnn_examples |
Time series forecasting using GRNN regression | grnn_forecasting |
Training examples and their corresponding weights used in a prediction | grnn_weights |
Plot an example used in a prediction of a grnnForecast object | plot_example |
Plot the prediction for a test set | plot.grnnForecastRO |
Predict method for GRNN models for time series forecasting. | predict.grnnForecast |
Assessing forecasting accuracy with rolling origin | rolling_origin |