Time series modeling and forecasting of the consumer price index Bandar Lampung

The aims of this study are to find the best Time Series model for forecasting the Consumer Price Index (CPI). To find the best model, first we evaluate the stationary of the data by using time series plot, Autocorrelation Function (ACF), and Unit root Test. Then the Time Series model was found by us...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلفون الرئيسيون: Kharimah, Faiga, Usman, Mustofa, Widiarti, Widiarti, Elfaki, Faiz Ahmed Mohamed
التنسيق: مقال
اللغة:English
منشور في: Sci.Int.(Lahore) 2015
الموضوعات:
الوصول للمادة أونلاين:http://irep.iium.edu.my/46113/1/Faiga_SI_section_B_4619-.pdf
http://irep.iium.edu.my/46113/
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الوصف
الملخص:The aims of this study are to find the best Time Series model for forecasting the Consumer Price Index (CPI). To find the best model, first we evaluate the stationary of the data by using time series plot, Autocorrelation Function (ACF), and Unit root Test. Then the Time Series model was found by using ACF and Partial Autocorrelations Function (PACF). The best model was found by using the criteria: Mean Squares Error (MSE), Akaike Information Criteria (AIC) and Bayesian Information Criterion (BIC. Based on this criteria the best modelfound in this paper is ARIMA (1,1,0) compare to ARIMA (0,1,1), and ARIMA(1,1,1).