Forecasting

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Forecasting is the process of estimation in unknown situations. Prediction is a similar, but more general term, and usually refers to estimation of time series, cross-sectional or longitudinal data. Forecasting is commonly used in discussion of time-series data.^[1]

The main source of information about forecasting on the internet is the Forecasting Principles site, forecastingprinciples.com. Forecasting Principles summarizes all useful knowledge about forecasting for researchers, practitioners, and educators. It is provided as a public service by the International Institute of Forecasters. The Institute publishes the journals International Journal of Forecasting and Foresight, and organizes International Symposia on Forecasting and forecasting workshops.

Contents 1 Categories of forecasting methods 1.1 Time series methods 1.2 Causal / econometric methods 1.3 Judgemental methods 1.4 Other methods 2 Forecasting accuracy 3 Application of forecasting 4 References 5 See also 6 External links

[edit] Categories of forecasting methods

[edit] Time series methods

Time series methods use historical data as the basis for estimating future outcomes.

• Moving average
• Exponential smoothing
• Extrapolation
• Linear prediction
• Trend estimation
• Growth curve

[edit] Causal / econometric methods

Some forecasting methods use the assumption that it is possible to identify the underlying factors that might influence the variable that is being forecasted. For example, sales of umbrellas might be associated with weather conditions. If the causes are understood, projections of the influencing variables can be made and used in the forecast.

• Regression analysis using linear regression or non-linear regression
• Autoregressive moving average (ARMA)
• Autoregressive integrated moving average (ARIMA)

e.g. Box-Jenkins

• Econometrics

[edit] Judgemental methods

Judgemental forecasting methods incorporate intuitive judgements, opinions and probability estimates.

• Composite forecasts
• Surveys
• Delphi method
• Scenario building
• Technology forecasting
• Forecast by analogy

[edit] Other methods

• Simulation
• Prediction market
• Probabilistic forecasting and Ensemble forecasting

[edit] Forecasting accuracy

The forecast error is the difference between the forecast value and the actual value for the corresponding period.

where E is the forecast error at period t, Y is the actual value at period t, and F is the forecast for period t.

Measures of aggregate error:

Mean Absolute Error (MAE)
Mean Absolute Percentage Error (MAPE)
Mean squared error (MSE)
Root Mean squared error (RMSE)

See also

• Forecast error
• Predictability
• Prediction interval, similar to confidence interval

[edit] Application of forecasting

Forecasting has application in many situations:

• Weather forecasting and Metereology
• Transport planning and Transportation forecasting
• Economic forecasting
• Technology forecasting
• Earthquake prediction
• Land use forecasting
• Product forecasting

[edit] References

1. ^ http://armstrong.wharton.upenn.edu/dictionary/bin/search.pl

• Armstrong, J. Scott (ed.) (2001). Principles of forecasting: a handbook for researchers and practitioners (in English). Norwell, Massachusetts: Kluwer Academic Publishers. ISBN 0-7923-7930-6.

• Kress, George J., Snyder, John (30 May 1994). Forecasting and market analysis techniques: a practical approach (in English). Westport, Connecticut, London: Quorum Books. ISBN 089930835X.

• Geisser, Seymour (1 June 1993). Predictive Inference: An Introduction (in English). Chapman & Hall, CRC Press. ISBN 0412034719.

[edit] See also

• CPFR
• Prediction
• Predictive analytics
• Prognosis
• Estimation

[edit] External links

• The International Institute of Forecasters
• Forecasting Principles: "Evidence-based forecasting"
• Long-Range Forecasting: "The accumulated wisdom of ages... about forecasting methods"
• Principles of Forecasting Handbook
• http://www.statsoft.com/textbook/sttimser.html