tsfgrnn
1.0.5Time Series Forecasting Using GRNN
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-04-2212 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1811 OK · 2 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- References docs
- 13%
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Checks run against github.com/franciscomartinezdelrio/tsfgrnn on 2026-07-31.
Dependencies
Nothing depends on this yet.
Code & Tests
People & History
6 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 1.0.5Latest
- RR 4.3.0 released · 2023-04-21
- 1.0.42023-03-24 · diff ↗
- 1.0.22022-05-30 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.12021-04-22 · diff ↗
- 1.0.02021-03-08 · diff ↗
- RR 4.0.0 released · 2020-04-24
- 0.1.02019-11-25
- RR 3.6.0 released · 2019-04-26
Package metadata
- First published
- 2019-11-25
- Total releases
- 6 / 7 yrs
- License
- GPL-2 OSI
- Download size
- 82 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet