Application of Autoregressive Integrated Moving Average Model and Weighted Markov Chain on Forecasting Under-Five Mortality Rates in Nigeria (Published)
The aim of this study is to obtain an optimal model between the traditional time series model (ARIMA) and Weighted Markov Chain. The historical dataset of U5MR in Nigeria from 1980-2019 is obtained from the official website of World Bank. ARIMA modeling involved differencing of the data to attain stationarity, while WMC involved classification of the datasets into clusters using k-means cluster analysis and transition of states. Two performance measures Theil’s U Statistic and MAPE are used to evaluate the two models based on in-sample and out-sample. The results shows that ARIMA(0,3,2) is a better model to forecast U5MR in Nigeria.
Keywords: ARIMA, K-Mean Cluster, MAPE, Theil’s U Statistic, U5MR, Weighted Markov Chain (WMC)
On Forecasting Infant Mortality Rate by Sex using ARIMA Model: A Case of Nigeria (Published)
This paper examines the application of ARIMA model on forecasting Infant Mortality Rate (IMR) in Nigeria. It undertakes a comparison of Male and Female. The data used were obtained from the website of the World Bank. The data consist of annual Infant Mortality Rate (per 1000 live births) on Male and Female from 1980 to 2019. Akaike’s Information Criterion (AIC) was used to select the best model and Time Series Plot, Residual Plot and the Histogram for Residuals were used to check the forecast adequacy of the selected models. The results of this study showed that the Infant Mortality Rate (IMR) on Male and Female attain stationarity after the second differencing. ARIMA (2,2,0) with AIC of -9.94 and ARIMA (1,2,0) with AIC of -13.10 were selected for forecasting Infant Mortality Rate for Male and Female respectively. The results further showed that the selected ARIMA models are adequate for forecasting male and female Infant Mortality Rate, and that by 2030, Male infant mortality rate will decline to 58.54 per 1000 live births while Female infant mortality rate will decline to 44.50 per 1000 live births.
Keywords: ARIMA, Female, Forecasting, Infant Mortality Rate, Male, Nigeria
Modeling and Forecasting of Armed Robbery Cases in Nigeria using Auto Regressive Integrated Moving Average (ARIMA) Models. (Published)
We have utilized a twenty-nine year crime data in Nigeria pertaining to Armed Robbery, the study proposes crime modeling and forecasting using Autoregressive Integrated Moving Average Models, the best model were selected based on the minimum Akaike information criteria (AIC), Bayesian information criteria(BIC), and Hannan-Quinn criteria (HQC) values and was used to make forecast. Forecasted values suggest that Armed Robbery would slightly be on the increase
Keywords: ACF/PACF, ARIMA, Akaike information criteria, Bayesian information criteria, Forecasting, Hannan-Quinn criteria, armed robbery, crime rate