Empirical Comparisons of Univariate Exponential Smoothing and Moving Average Methods for Forecasting Crime Rate

Abstract

The purpose of this research paper is to carry out comparative analysis and evaluation of some univariate time series models suitable for forecasting crime rate, and determine the most appropriate forecasting method. Moving average methods and Exponential smoothing methods of forecasting were used on monthly crime data obtained in Ekiti State of Nigeria from January, 2004 to December, 2012. The accuracy of the forecasting methods was measured using Mean Forecast Error (MFE), Mean Absolute Deviation (MAD), Mean Square Error (MSE) and Root Mean Square Error (RMSE). The result showed that 3-month moving average method produced the most accurate forecasting based on the data obtained in the ranking table.