Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data

Mary Pleños

doi:10.22630/PRS.2022.22.2.6

PDF (English)

Opublikowane:

Jun 30, 2022

Numer

Tom 22 Nr 2 (2022)

Dział

Articles

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Mary Pleños

Visayas State University, Philippines

https://orcid.org/0000-0002-8378-2663

DOI: https://doi.org/10.22630/PRS.2022.22.2.6

Abstrakt

This study utilized the data on abaca fiber production and used Holt-Winters model to forecast the abaca fiber production since the studied variable is characterized by a fairly strong intensity of seasonality. For the construction of forecasts, additive and multiplicative models were used. The most accurate forecasts were selected on the basis of Mean Square Error, Root Mean Square Error, Mean Absolute Percentage Error, and Mean Absolute Scaled Error. It was found that the multiplicative method had a higher accuracy, hence it was utilized to forecast the production for the next three years. According to the findings, the anticipated fiber production for 2021-2023 showed an increase up to the second quarter, but then declining afterwards.

Jak cytować

Pleños, M. (2022). Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data. Zeszyty Naukowe SGGW W Warszawie - Problemy Rolnictwa Światowego, 22(2), 17–29. https://doi.org/10.22630/PRS.2022.22.2.6

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