Comparison of Exponential Smoothing Models for Forecasting Cassava Production

O.V. Oni¹ , Y.O. Akanle²

1. Department of Statistics, Federal College of Animal Health and Production Technology, Ibadan.
2. Department of Statistics, Federal College of Animal Health and Production Technology, Ibadan.

Section:Research Paper, Product Type: Isroset-Journal
Vol.5 , Issue.3 , pp.65-68, Jun-2018

CrossRef-DOI:   https://doi.org/10.26438/ijsrmss/v5i3.6568

Online published on Jun 30, 2018

Copyright © O.V. Oni , Y.O. Akanle . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
This paper evaluated and compared the performance of a family of smoothing models such as Simple Exponential Smoothing (SES), Holt’s Linear Trend (HLT), Exponential trend (ET) and Holt’s Damped Methods: additive and multiplicative; to forecast the annual Cassava production in Nigeria. The predictive capabilities were compared in terms of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Percentage Error (MPE) and Mean Absolute Percentage Error (MAPE) based on the validated data set. The Holt’s Exponential Trend with parameter α=0.8556 and β=0.0001 was found to have best described the data having the lowest ranked error statistics in an out of sample performance.

Key-Words / Index Term :
Cassava, Simple Exponential Smoothing, Holt’s Linear Trend, Exponential Trend, Holt’s Damped Additive and Holt’s Damped Multiplicative

References :
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