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.
- Version1.0.5
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- tsfgrnn citation info
- Last release02/15/2024
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Team
Francisco Martinez
Antonio Conde-Sanchez
Show author detailsRolesAuthorAna Maria Martinez-Rodriguez
Show author detailsRolesAuthorMaria Pilar Frias-Bustamante
Show author detailsRolesAuthor
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