COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES

In the food industry, inventory models that provide adequate prediction of demand are useful for optimum supply management, especially in perishable products such as dairy products, because of their short shelf life and the importance of their quality related to health. However, some small and mediu...

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Main Authors: Marisol Valencia Cárdenas, Victor Alfonso Osorno Vásquez, Juan Carlos Salazar Uribe
Format: Article
Language:Spanish
Published: Universidad Nacional de Colombia, sede Medellín 2017-07-01
Series:Revista de la Facultad de Ciencias
Subjects:
Online Access:https://revistas.unal.edu.co/index.php/rfc/article/view/66085
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author Marisol Valencia Cárdenas
Victor Alfonso Osorno Vásquez
Juan Carlos Salazar Uribe
author_facet Marisol Valencia Cárdenas
Victor Alfonso Osorno Vásquez
Juan Carlos Salazar Uribe
author_sort Marisol Valencia Cárdenas
collection DOAJ
description In the food industry, inventory models that provide adequate prediction of demand are useful for optimum supply management, especially in perishable products such as dairy products, because of their short shelf life and the importance of their quality related to health. However, some small and medium Colombian companies do not have the technology and capabilities to do forecasts of their products, which is very important for production and inventory planning. In this paper we propose a comparison of the precision of forecasts of individual statistical models and combinations between them, using a multi-product algorithm for the combinations applied to a case study of sales of the dairy sector. It is found that an individual model of Bayesian regression with innovation is a very good alternative in the case studied, as well as two of the combination techniques used.
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spelling doaj.art-a9fb6e25aa624158a70337a57079939b2022-12-21T23:07:40ZspaUniversidad Nacional de Colombia, sede MedellínRevista de la Facultad de Ciencias0121-747X2357-55492017-07-016212414010.15446/rev.fac.cienc.v6n2.6608546913COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUESMarisol Valencia Cárdenas0Victor Alfonso Osorno Vásquez1Juan Carlos Salazar Uribe2Institución Universitaria Tecnológico de AntioquiaUniversidad Nacional de ColombiaUniversidad Nacional de Colombia, Sede MedellínIn the food industry, inventory models that provide adequate prediction of demand are useful for optimum supply management, especially in perishable products such as dairy products, because of their short shelf life and the importance of their quality related to health. However, some small and medium Colombian companies do not have the technology and capabilities to do forecasts of their products, which is very important for production and inventory planning. In this paper we propose a comparison of the precision of forecasts of individual statistical models and combinations between them, using a multi-product algorithm for the combinations applied to a case study of sales of the dairy sector. It is found that an individual model of Bayesian regression with innovation is a very good alternative in the case studied, as well as two of the combination techniques used.https://revistas.unal.edu.co/index.php/rfc/article/view/66085Estadística y probabilidadevaluación de modelos y selecciónmétodos de pronósticoestadística Bayesiana.
spellingShingle Marisol Valencia Cárdenas
Victor Alfonso Osorno Vásquez
Juan Carlos Salazar Uribe
COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
Revista de la Facultad de Ciencias
Estadística y probabilidad
evaluación de modelos y selección
métodos de pronóstico
estadística Bayesiana.
title COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
title_full COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
title_fullStr COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
title_full_unstemmed COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
title_short COMPARATIVE OF FORECASTING MODELS: CLASSICAL, BAYESIAN, AND COMBINATION TECHNIQUES
title_sort comparative of forecasting models classical bayesian and combination techniques
topic Estadística y probabilidad
evaluación de modelos y selección
métodos de pronóstico
estadística Bayesiana.
url https://revistas.unal.edu.co/index.php/rfc/article/view/66085
work_keys_str_mv AT marisolvalenciacardenas comparativeofforecastingmodelsclassicalbayesianandcombinationtechniques
AT victoralfonsoosornovasquez comparativeofforecastingmodelsclassicalbayesianandcombinationtechniques
AT juancarlossalazaruribe comparativeofforecastingmodelsclassicalbayesianandcombinationtechniques