Time Series Modelling of Monthly Temperature Data of Jerusalem/Palestine.

Abstract

The objective of the research is to estimate the month-ahead temperature records in Jerusalem, Palestine. In this study, the modeling mechanism of analytic for forecasting is considered. This paper explores implementation of ARIMA and GARCH modeling techniques to fit a historical data set and estimate the coefficients of the suitable models for fitting the average monthly temperature data of Jerusalem in Palestine for the period from January 1964 to December 2013. The analysis of this study are carried out with the assist of R software. Eventually, using different statistical measures, comparison efficiency between ARIMA $\(2, 0, 1)(2, 1, 1) _ {12} $ and AR (1)-GARCH (1, 1) models are produced. AR (1)-GARCH (1, 1) is detected to be a better than ARIMA $\(2, 0, 1)(2, 1, 1) _ {12} $ model.