Time Series Forecasting using ARIMA-ANN Hybrid Model
Overview
Testing, Implementation, and Forecasting of the ARIMA-ANN hybrid model. The ARIMA-ANN hybrid model combines the distinct strengths of the Auto-Regressive Integrated Moving Average (ARIMA) model and the Artificial Neural Network (ANN) model for time series forecasting.For method details see Zhang, GP (2003) doi:10.1016/S0925-2312(01)00702-0.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-06-09
- ERROR12 OK, 1 ERROR2026-06-08
- OK14 OK2026-03-10
Documentation
- Help pages
- 1
- Examples that run
- 100%1 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 100%
Downloads
Dependencies
Installing ARIMAANN adds 35 packages (22 with compiled code, 24 MB of source tarballs). Heaviest: ggplot2 6.0 MB, colorspace 2.0 MB, Rcpp 1.8 MB.
Code & Tests
People & History
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.0Latest2022-10-13 · current release
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-10-13
- Total releases
- 1 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 2.3.1
- Download size
- 2.0 KB
Cite
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