Forecasting with Univariate Box - Jenkins Models


Book Description

Explains the concepts and use of univariate Box-Jenkins/ARIMA analysis and forecasting through 15 case studies. Cases show how to build good ARIMA models in a step-by-step manner using real data. Also includes examples of model misspecification. Provides guidance to alternative models and discusses reasons for choosing one over another.













Applied Time Series and Box-Jenkins Models


Book Description

This text presents Time Series analysis and Box-Jenkins models.




Box-Jenkins in Practice


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Short Term Forecasting


Book Description




Some Aspects of Applied Forecasting Methods


Book Description

This book has brought out inferential methods to forecasting with linear statistical and time series models, the various forecasting methods existing in the literature have been briefly reviewed with inferential problems on them. In view of the importance of forecasting is empirical research, some new procedures for applied forecasting have been developed.Here, these techniques are developed by using Internally Studentized Residuals. Further, a modified Box-Jenkins methodology has been presented for auto Integrated Moving average model ARIMA(p, d, q) based on Internally Studentized Residuals. Under Diagnostic checking, a modified L Jung and Box statistic for testing the residuals has been proposed. The forecasts to be obtained from this methodology may be used as benchmark to compare with forecasts to be yielded by other forecasting technique