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Using Box-Jenkins Models to Forecast Mobile Cellular Subscription

DOI: 10.4236/ojs.2016.62026, PP. 303-309

Keywords: Mobile Cellular Subscription, Box-Jenkins Methodology, ARIMA Model, Autocorrelation Function, Partial Autocorrelation Function

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Abstract:

In this paper, the Box-Jenkins modelling procedure is used to determine an ARIMA model and go further to forecasting. The mobile cellular subscription data for the study were taken from the administrative data submitted to the Zambia Information and Communications Technology Authority (ZICTA) as quarterly returns by all three mobile network operators Airtel Zambia, MTN Zambia and Zamtel. The time series of annual figures for mobile cellular subscription for all mobile network operators is from 2000 to 2014 and has a total of 15 observations. Results show that the ARIMA (1, 2, 1) is an adequate model which best fits the mobile cellular subscription time series and is therefore suitable for forecasting subscription. The model predicts a gradual rise in mobile cellular subscription in the next 5 years, culminating to about 9.0% cumulative increase in 2019.

References

[1]  SAS Institute Inc. (2014) SAS/ETS 13.2 User’s Guide: The ARIMA Procedure. SAS Institute Inc., Cary.
[2]  Box, G.E. and Jenkins, G.M. (1994) Time Series Analysis: Forecasting and Control. 3rd Edition, Prentice Hall, Englewood Cliffs.
[3]  Wei, W. (1990) Time Series Analysis: Univariate and Multivariate Methods. Addison-Wesley Publishing Company, Inc., New York.

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