ATAforecasting
0.0.61Automatic Time Series Analysis and Forecasting using the Ata Method
Overview
The Ata method (Yapar et al. (2019) doi:10.15672/hujms.461032), an alternative to exponential smoothing (described in Yapar (2016) doi:10.15672/HJMS.201614320580, Yapar et al. (2017) doi:10.15672/HJMS.2017.493), is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing forecasting methods. Forecasting performance of the Ata method is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or seasonal time series which can be decomposed into four components (remainder, level, trend and seasonal). This methodology performed well on the M3 and M4-competition data. This package was written based on Ali Sabri Taylan’s PhD dissertation.
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- OK2026-06-0913 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0812 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-04-2214 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-04-1813 OK · 0 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- OK2026-03-1014 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 99%
- Return-value docs
- 100%
- References docs
- 38%
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Checks run against github.com/alsabtay/ataforecasting on 2026-07-19.
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Code & Tests
People & History
8 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 0.0.61Latest
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- 0.0.602023-06-12 · diff ↗
- RR 4.3.0 released · 2023-04-21
- 0.0.572022-04-22 · diff ↗
- RR 4.2.0 released · 2022-04-22
- 0.0.562021-12-08 · diff ↗
- 0.0.552021-10-22 · diff ↗
- 0.0.542021-10-20 · diff ↗
- 0.0.532021-10-11 · diff ↗
- RR 4.1.0 released · 2021-05-18
- 0.0.522021-03-08
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-03-08
- Total releases
- 8 / 5 yrs
- License
- GPL (>= 3) OSI
- Minimum R
- ≥ 4.1
- Bundled data
- 3.1 KB / 2 files
- Download size
- 130 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet