European Journal of Statistics and Probability (EJSP)

EA Journals


Modelling and Forecasting Inflation Rates in Kenya Using ARIMA Model (Published)

This research aimed to develop an ARIMA(1,0,11) model for forecasting inflation rates in Kenya. The research utilized historical inflation data from January 2005 to August 2022 to develop the model and evaluated its performance on a test set spanning from September 2022 to August 2023. The results demonstrated that the ARIMA model provided accurate forecasts, with low forecast errors in terms of MSE, RMSE, MAE, and MAPE. These forecasts have practical utility for various stakeholders, including policymakers, businesses, and financial institutions, as they can use the information to inform pricing strategies, interest rate policies, and other economic decisions. Additionally, the study highlighted the importance of data quality, continuous monitoring of economic factors, and periodic model refinement to ensure the effectiveness of inflation forecasting in a dynamic economic environment.

Keywords: Arima model, Forecasting, Kenya, Modelling, inflation rates

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

A Suggested Approach to Artificial Neural Networks Modeling of Time Series (Published)

This research proposed a method of selecting an optimal combination of numbers of input (number of lagged values in the model) and of hidden nodes for modeling seasonal data using Artificial Neural Networks (ANN). Three data sets (rainfall, relative humidity and solar radiation) were used in assessing the proposed procedure and the resulting ANN models were compared with two traditional models (Holt-Winter’s and SARIMA). Models with large number of lagged values have shown tendency to outperform those with small number of lagged values. Selected ANN model was found to outperform the two traditional models on rainfall data; it performed better than SARIMA but worse than Holt-Winter’s model on relative humidity data and performed worse than the two methods on solar radiation data. The proposed procedure has hence, performed fairly well. Oscillatory performance recorded by ANN models that resulted from the proposed procedure in relation to the other two models only attests to the fact that no particular model is best on every data set. Rather than insist on elegance or sophistication, researchers should be guided by parsimony.

Keywords: Artificial Neural Networks, Forecasting, SARIMA, holt-winter, seasonal data

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

Scroll to Top

Don't miss any Call For Paper update from EA Journals

Fill up the form below and get notified everytime we call for new submissions for our journals.