Time Series Modelling of Monthly average Temperature in Gaborone-Botswana

K. Sediakgotla, W. Molefe, D. K. Shangodoyin
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Abstract

The seasonal series on the average maximum temperatures in Gaborone (Botswana) is used to identify the best time series model that can be used for forecasting. The series was found to be highly seasonal. Seasonally adjusting the series prior to applying the Box and Jenkins procedure did not average out the seasonal effects, despite giving a fairly good ARIMA(1,1,1). We also fitted SARIMA(p,d,q)(P,D,Q) with seasonality effects at lags s=12,24,36. Correlograms, Dickey Fuller tests and other model comparison methods led to an ARIMA(1,1,1)(0,1,1)[12]. The seasonal multiplicative SARIMA was found to be parsimonious as compared to an additive seasonal SARIMA.
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哈博罗内-博茨瓦纳月平均气温的时间序列模拟
利用哈博罗内(博茨瓦纳)平均最高气温的季节序列来确定可用于预报的最佳时间序列模型。人们发现这个系列具有很强的季节性。尽管给出了相当好的ARIMA(1,1,1),但在应用Box和Jenkins程序之前对序列进行季节性调整并没有平均季节性影响。我们还拟合了SARIMA(p,d,q)(p,d,q)在滞后时间s=12,24,36时的季节性效应。相关图、Dickey Fuller检验等模型比较方法得到ARIMA(1,1,1)(0,1,1)[12]。发现季节性乘法SARIMA比加性季节性SARIMA更节俭。
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