Volume 4, Issue 2, April 2016, Page: 52-58
Statistical Modeling of Quarterly Record of Rainfall Distribution in South West Nigeria
Iyabode Favour Oyenuga, Department of Mathematics and Statistics, the Polytechnic, Ibadan, Nigeria
Benjamin Agboola Oyejola, Department of Statistics, University of Ilorin, Kwara State, Nigeria
Johnson Taiwo Olajide, Department of Mathematics and Statistics, the Polytechnic, Ibadan, Nigeria
Received: Feb. 26, 2016;       Accepted: Mar. 10, 2016;       Published: Mar. 29, 2016
DOI: 10.11648/j.sjams.20160402.16      View  3347      Downloads  101
Abstract
Modelling distribution of rainfall in South West Nigeria is examined. Quarterly rainfall distribution data of Ibadan as a case study were collected for a period of 43 years (1971-2013) from Nigeria Meteorological Agency (NMA) quoted in Central Bank of Nigeria (CBN) bulletin. The time series analysis was used to model and forecast the quarterly rainfall. The time plot shows there is a seasonal cycles in the series, we used Akaike Information Criterion to detect auto-regressive (AR), moving average (MA) and auto-regressive moving average (ARMA) models of the best order. It was shown that AR(4), MA(4) and ARMA(4,4) have the least Akaike Information Criterion (AIC). These models were then used to forecast for the quarterly rainfall for five years.
Keywords
Akaike Information Criterion, AR Model, MA Model, ARMA Model, Forecasting, Rainfall
To cite this article
Iyabode Favour Oyenuga, Benjamin Agboola Oyejola, Johnson Taiwo Olajide, Statistical Modeling of Quarterly Record of Rainfall Distribution in South West Nigeria, Science Journal of Applied Mathematics and Statistics. Vol. 4, No. 2, 2016, pp. 52-58. doi: 10.11648/j.sjams.20160402.16
Copyright
Copyright © 2016 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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