ATAforecasting
Automatic Time Series Analysis and Forecasting using the Ata Method
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.
- Version0.0.60
- R version≥ 4.1
- LicenseGPL (≥ 3)
- Needs compilation?Yes
- Yapar et al. (2019)
- Yapar (2016)
- Yapar et al. (2017)
- Last release06/12/2023
Documentation
Team
Ali Sabri Taylan
Hanife Taylan Selamlar
Guckan Yapar
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- Imports10 packages
- Linking To2 packages
- Reverse Depends1 package