alsabtay/ATAforecasting: Forecasting Time Series by ATA Method

Based on the modified simple exponential smoothing as described in Yapar, G. (2016). ATA method is a new univariate time series forecasting method which provides innovative solutions to issues faced during the initialization and optimization stages of existing methods. ATA forecasting performance is superior to existing methods both in terms of easy implementation and accurate forecasting. It can be applied to non-seasonal or deseasonalized time series, where the deseasonalization can be performed via any preferred decomposition method. This methodology performed extremely well on the M3 and M4-competition data.

Getting started

Package details

AuthorAli Sabri Taylan <[email protected]> and Hanife Taylan Selamlar <[email protected]>
MaintainerAli Sabri Taylan <[email protected]>
LicenseGPL-3
Version0.0.47
URL https://github.com/alsabtay/ATAforecasting
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("alsabtay/ATAforecasting")
alsabtay/ATAforecasting documentation built on Nov. 6, 2019, 4:52 p.m.