MODELLING AND FORECASTING MORTALITY RATE DUE TO MALARIA INFECTION, USING AUTOREGRESSIVE MOVING AVERAGE (ARMA) MODELS A PANACEA TO NIGERIAN SOCIO-ECONOMIC CHALLENGES

Adeboye, Nurain Olawale (2017) MODELLING AND FORECASTING MORTALITY RATE DUE TO MALARIA INFECTION, USING AUTOREGRESSIVE MOVING AVERAGE (ARMA) MODELS A PANACEA TO NIGERIAN SOCIO-ECONOMIC CHALLENGES. In: National Conference on Science, Technology and Communication, 2017, Federal Polytechnic, Ilaro.

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Abstract

This research work was based on fitting Autoregressive moving average (ARMA) model and the forecasting of Mortality rate due to Malaria infections in Nigeria, using the medical records of General Hospital Ifo, Ogun state between January 2009 to December 2015, with the aim of recommending adequate checks in possible malaria escalation around the globe. Based on the plotted Autocorrelation functions (ACF) graph of the original series and the Augmented Dickey Fuller (ADF) test carried out, it was observed that the series was non-stationary which necessitated the series to be differenced to attain stationarity. This stationary series data was modelled in order to determine the stability of the parameters estimation. The plots of the ordinary and differenced series autocorrelation and partial autocorrelation functions suggested some models for selection but the Akaike and Bayesian Information Criterion was used to select the model that really provided the best fit for the series. ARMA (1,1) was found to be best fitted model as a result of their lower AIC and BIC values, and this was used for future forecast. The result shows that the distribution of forecast 2 tend to follow a downward trend with ±2 standard error limit. Therefore, there is high tendency for mortality rate due to malaria infection to reduce drastically between the forecasted periods of 2016 – 2018.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics
Divisions:	Faculty of Engineering, Science and Mathematics > School of Mathematics
Depositing User:	Mr Taiwo Egbeyemi
Date Deposited:	13 Jul 2020 11:33
Last Modified:	13 Jul 2020 11:33
URI:	http://eprints.federalpolyilaro.edu.ng/id/eprint/1004

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