Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru

Humberto Sernaqué; Moly Meca; Eduardo Zapata; Berenise Marchan; Junior Medina; Denis Nole; Cristhian Aldana; Yesenia Saavedra; Luis Trelles; Nelson Chuquihuanca; Gustavo Mendoza

doi:10.54941/ahfe1001007

Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru

Humberto Sernaqué
, Moly Meca
, Eduardo Zapata
, Berenise Marchan
, Junior Medina
, Denis Nole
, Cristhian Aldana
, Yesenia Saavedra
, Luis Trelles
, Nelson Chuquihuanca
, Gustavo Mendoza

Universidad Nacional de Frontera

Universidad Nacional de Frontera

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Agricultural commodities present remarkable volatility in their production levels, which severely affects farmers. The variational dynamics in the prices of the inputs used and the constant variations in weather conditions have a significant influence on the cereal production chain in Peru; therefore, compared to the ARIMA model, the Additive Holt-Winters forecasting model presented a better fit according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), forecasting the production of Oryza sativa, Zea mays L. var. Indurata and Amaranthus caudatus; however, due to the high seasonality, volatility of production, and the greater amount of outliers due to production in certain periods and geographical areas, the Holt-Winters Multiplicative model predicted the national production of Zea mays L. ssp amiláceo and Chenopodium quinoa, in Peru in the period 2000-2021.

Original language	English
Title of host publication	Applied Human Factors and Ergonomics International
Publisher	AHFE International
DOIs	https://doi.org/10.54941/ahfe1001007
State	Published - 2022

Publication series

Name	Applied Human Factors and Ergonomics International
Volume	22
ISSN (Electronic)	2771-0718

Keywords

AIC
ARIMA
BIC
cereals
forecasting
Holt-Winters
production

Access to Document

10.54941/ahfe1001007

Cite this

Sernaqué, H., Meca, M., Zapata, E., Marchan, B., Medina, J., Nole, D., Aldana, C., Saavedra, Y., Trelles, L., Chuquihuanca, N., & Mendoza, G. (2022). Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru. In Applied Human Factors and Ergonomics International (Applied Human Factors and Ergonomics International; Vol. 22). AHFE International. https://doi.org/10.54941/ahfe1001007

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title = "Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru",

abstract = "Agricultural commodities present remarkable volatility in their production levels, which severely affects farmers. The variational dynamics in the prices of the inputs used and the constant variations in weather conditions have a significant influence on the cereal production chain in Peru; therefore, compared to the ARIMA model, the Additive Holt-Winters forecasting model presented a better fit according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), forecasting the production of Oryza sativa, Zea mays L. var. Indurata and Amaranthus caudatus; however, due to the high seasonality, volatility of production, and the greater amount of outliers due to production in certain periods and geographical areas, the Holt-Winters Multiplicative model predicted the national production of Zea mays L. ssp amil{\'a}ceo and Chenopodium quinoa, in Peru in the period 2000-2021.",

keywords = "AIC, ARIMA, BIC, cereals, forecasting, Holt-Winters, production",

author = "Humberto Sernaqu{\'e} and Moly Meca and Eduardo Zapata and Berenise Marchan and Junior Medina and Denis Nole and Cristhian Aldana and Yesenia Saavedra and Luis Trelles and Nelson Chuquihuanca and Gustavo Mendoza",

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series = "Applied Human Factors and Ergonomics International",

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Sernaqué, H, Meca, M, Zapata, E, Marchan, B, Medina, J, Nole, D, Aldana, C , Saavedra, Y, Trelles, L, Chuquihuanca, N & Mendoza, G 2022, Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru. in Applied Human Factors and Ergonomics International. Applied Human Factors and Ergonomics International, vol. 22, AHFE International. https://doi.org/10.54941/ahfe1001007

Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru. / Sernaqué, Humberto; Meca, Moly; Zapata, Eduardo et al.
Applied Human Factors and Ergonomics International. AHFE International, 2022. (Applied Human Factors and Ergonomics International; Vol. 22).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

TY - CHAP

T1 - Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru

AU - Sernaqué, Humberto

AU - Meca, Moly

AU - Zapata, Eduardo

AU - Marchan, Berenise

AU - Medina, Junior

AU - Nole, Denis

AU - Aldana, Cristhian

AU - Saavedra, Yesenia

AU - Trelles, Luis

AU - Chuquihuanca, Nelson

AU - Mendoza, Gustavo

PY - 2022

Y1 - 2022

N2 - Agricultural commodities present remarkable volatility in their production levels, which severely affects farmers. The variational dynamics in the prices of the inputs used and the constant variations in weather conditions have a significant influence on the cereal production chain in Peru; therefore, compared to the ARIMA model, the Additive Holt-Winters forecasting model presented a better fit according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), forecasting the production of Oryza sativa, Zea mays L. var. Indurata and Amaranthus caudatus; however, due to the high seasonality, volatility of production, and the greater amount of outliers due to production in certain periods and geographical areas, the Holt-Winters Multiplicative model predicted the national production of Zea mays L. ssp amiláceo and Chenopodium quinoa, in Peru in the period 2000-2021.

AB - Agricultural commodities present remarkable volatility in their production levels, which severely affects farmers. The variational dynamics in the prices of the inputs used and the constant variations in weather conditions have a significant influence on the cereal production chain in Peru; therefore, compared to the ARIMA model, the Additive Holt-Winters forecasting model presented a better fit according to the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC), forecasting the production of Oryza sativa, Zea mays L. var. Indurata and Amaranthus caudatus; however, due to the high seasonality, volatility of production, and the greater amount of outliers due to production in certain periods and geographical areas, the Holt-Winters Multiplicative model predicted the national production of Zea mays L. ssp amiláceo and Chenopodium quinoa, in Peru in the period 2000-2021.

KW - AIC

KW - ARIMA

KW - BIC

KW - cereals

KW - forecasting

KW - Holt-Winters

KW - production

UR - https://www.scopus.com/pages/publications/105036120300

U2 - 10.54941/ahfe1001007

DO - 10.54941/ahfe1001007

M3 - Capítulo

AN - SCOPUS:105036120300

T3 - Applied Human Factors and Ergonomics International

BT - Applied Human Factors and Ergonomics International

PB - AHFE International

ER -

Comparison of Arima and Holt-Winters forecasting models for time series of cereal production in Peru

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Keywords

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