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ATAforecasting
View on CRAN: Click
here
Download and install ATAforecasting package within the R console
Install from CRAN:
install.packages("ATAforecasting")
Install from Github:
library("remotes")
install_github("cran/ATAforecasting")
Install by package version:
library("remotes")
install_version("ATAforecasting", "0.0.60")
Attach the package and use:
library("ATAforecasting")
Maintained by
Ali Sabri Taylan
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
10.32614/CRAN.package.ATAforecasting . https://github.com/alsabtay/ATAforecasting/issues . https://github.com/alsabtay/ATAforecasting . ATAforecasting results . ATAforecasting.pdf . ATAforecasting_0.0.60.tar.gz . ATAforecasting_0.0.60.zip . ATAforecasting_0.0.60.zip . ATAforecasting_0.0.60.zip . ATAforecasting_0.0.60.tgz . ATAforecasting_0.0.60.tgz . ATAforecasting_0.0.60.tgz . ATAforecasting_0.0.60.tgz . ATAforecasting archive . https://CRAN.R-project.org/package=ATAforecasting .
First Published: 2021-03-08
Latest Update: 2023-06-12
Description:
The Ata method (Yapar et al. (2019) ), an alternative to exponential smoothing (described in Yapar (2016) ,
Yapar et al. (2017) ), 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
How to cite:
Ali Sabri Taylan (2021). ATAforecasting: Automatic Time Series Analysis and Forecasting using the Ata Method. R package version 0.0.60, https://cran.r-project.org/web/packages/ATAforecasting. Accessed 06 May. 2025.
Previous versions and publish date:
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Other R packages that ATAforecasting depends,
imports, suggests or enhances
Complete documentation for ATAforecasting
Functions, R codes and Examples using
the ATAforecasting R package
Some associated functions: ATA.Accuracy . ATA.BackTransform . ATA.BoxCoxAttr . ATA.CI . ATA.Core . ATA.Decomposition . ATA.Forecast . ATA.Plot . ATA.Print . ATA.SeasAttr . ATA.Seasonality . ATA.Shift . ATA.Shift_Mat . ATA.Transform . ATA . ATAforecasting-package . find.freq.fourier . find.freq . find.multi.freq . fundingTR . touristTR .
Some associated R codes: ATA.R . ATA_Accuracy.R . ATA_Core.R . ATA_Find_Freq.R . ATA_Find_Freq_Fourier.R . ATA_Find_Multi_Freq.R . ATA_Forecast.R . ATA_SeasAttributes.R . ATA_Transform.R . ATAforecasting-package.R . RcppExports.R . SubATA_Damped.R . SubATA_Forecast.R . SubATA_Multiple.R . SubATA_MultipleO.R . SubATA_OneStepForecast.R . SubATA_Single.R . SubATA_SingleO.R . SubATA_Transform.R . data.R . Full ATAforecasting package functions and examples
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