ARIMAKnowledge Center 
Forecasting and estimating the future: AutoRegressive Integrated Moving Average. Explanation of ARIMA of Box and Jenkins. ('76) 
All about ARIMA. Join now. Completely free. 
Nobody can really look into the future. But modern statistical methods, econometric models, and Business Intelligence software can to some extent help businesses to forecast and to estimate what is going to happen in the future. ARIMA stands for AutoRegressive Integrated Moving Average. The ARIMA Time Series Analysis uses lags and shifts in the historical data
to uncover patterns (e.g. moving averages, seasonality) and predict the future.
The ARIMA model was first developed in the late 60s but it was systemized
by Box and Jenkins in 1976. ARIMA can be more complex to use than other statistical
forecasting techniques, although when implemented properly ARIMA can be quite
powerful and flexible. ARIMA is a method for determining two things:
For example y(t)= 1/3 * y(t3) + 1/3 * y(t2) + 1/3 * y(t1) is an ARIMA
model; another ARIMA MODEL is y(t)= 1/6 * y(t3) + 4/6 * y(t2) + 1/6 * y(t1) Book: Alan Pankratz  Forecasting with Univariate Box Jenkins Models : Concepts and Cases  Book: Jeffrey Wooldridge  Introductory Econometrics: A Modern Approach 
Compare with: Regression Analysis  Dynamic Regression  Exponential Smoothing  Analytical CRM  Business Intelligence Return to Management Hub: Finance & Investing  Marketing 

About 12manage  Advertising  Link to us / Cite us  Privacy  Suggestions  Terms of Service 