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2010 (Vol. 2, Issue: 1)
Article Information:

Short and Long Memory Time Series Models of Relative Humidity of Jos Metropolis

M.A. Chiawa, B.K. Asare and B. Audu
Corresponding Author:  Moses Chiawa 

Key words:  Precipitation, autocorrelation function, autocovariance, spectrum, periodogram, fractional integration,
Vol. 2 , (1): Page No: 23-31
Submitted Accepted Published
2009 October, 15 2009 November, 12 2010 March, 20
Abstract:

The percentage monthly relative humidity of Jos metropolis is examined in this study. Two models, a short memory seasonal autoregressive integrated moving average model [SARIMA(1,0,1)(2,1,2)] and long memory autoregressive fractional integrated moving average [ARFIMA(1,0.29,1)] are used to fit the same humidity data. Even though both models fit the data well, forecasts obtained from the ARFIMA(1,0.29,1) capture the swing in the data and resemble the actual values better than the forecasts using SARIMA(1,0,1)(2,1,2) model. This result shows that the Jos metropolitan data is better fitted by a long memory time series which captures the long swing in the weather data better than the short memory time series models whose effect quickly dies down.
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  Cite this Reference:
M.A. Chiawa, B.K. Asare and B. Audu, 2010. Short and Long Memory Time Series Models of Relative Humidity of Jos Metropolis.  Research Journal of Mathematics and Statistics, 2(1): Page No: 23-31.
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ISSN (Online):  2040-7505
ISSN (Print):   2042-2024
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