Journals / Hacettepe Journal of Mathematics and Statistics / 2019 / Cilt: 48 - Sayı: 6

ATA Method

Pages
1838–1844
Publication Date
2022-10-18
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Using the results from the M3-competition, the forecasting performance of this method will be compared to not only these two major approaches but also to other successful methods derived from these two approaches with respect to simplicity and cost in addition to accuracy.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, the forecasting accuracy of a new forecasting method that is alternative to two major forecasting approaches: exponential smoothing (ES) and ARIMA, will be evaluated.
📊
Key Findings & Data:In this study, the forecasting accuracy of a new forecasting method that is alternative to two major forecasting approaches: exponential smoothing (ES) and ARIMA, will be evaluated.
💡
Conclusion & Impact:Using the results from the M3-competition, the forecasting performance of this method will be compared to not only these two major approaches but also to other successful methods derived from these two approaches with respect to simplicity and cost in addition to accuracy.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Exponential smoothing · Forecasting · Initial value

Abstract

In this study, the forecasting accuracy of a new forecasting method that is alternative to two major forecasting approaches: exponential smoothing (ES) and ARIMA, will be evaluated. Using the results from the M3-competition, the forecasting performance of this method will be compared to not only these two major approaches but also to other successful methods derived from these two approaches with respect to simplicity and cost in addition to accuracy.

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Cite This Article

Yapar, G., Selamlar, H. T., Capar, S., Yavuz, İ. (2022). ATA Method. Hacettepe Journal of Mathematics and Statistics, Cilt: 48 - Sayı: 6, 1838–1844. https://ajindex.com/articles/530146

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