forecast n : a prediction about how something (as the weather) will develop [syn: prognosis]
1 predict in advance [syn: calculate]
3 indicate by signs; "These signs bode bad news" [syn: bode, portend, auspicate, prognosticate, omen, presage, betoken, foreshadow, augur, foretell, prefigure, predict]
estimate future conditions
- Afrikaans: voorspel
- Dutch: voorspellen
- Finnish: ennustaa, ennakoida
- French: prévoir
- German: vorhersagen, prognostizieren
- Indonesian: ramal, meramal, mengira, memperkirakan
- Italian: prevedere
- Japanese: 予想する (よそうする, yosō-suru)
- Norwegian: forutsi, predikere
- Spanish: predecir. pronosticar
- Swedish: förutsäga, förutse
Forecasting is the process of estimation in unknown situations. Prediction is a similar, but more general term. Both can refer to estimation of time series, cross-sectional or longitudinal data. Usage can differ between areas of application: for example in hydrology, the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specific future times, while the term "prediction" is used for more general estimates, such as the number of times floods will occur over a long period. Risk and uncertainty are central to forecasting and prediction. Forecasting is used in the practice of Customer Demand Planning in every day business forecasting for manufacturing companies. The discipline of demand planning, also sometimes referred to as supply chain forecasting, embraces both statistical forecasting and a consensus process.
Forecasting is commonly used in discussion of time-series data.
Categories of forecasting methods
Time series methods
Time series methods use historical data as the basis of estimating future outcomes.
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 forecast. 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
Judgemental forecasting methods incorporate intuitive judgements, opinions and probability estimates.
The forecast error is the difference between the actual value and the forecast value for the corresponding period.
\ E_t = Y_t - F_t
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:
Please note that the business forecasters and demand planners in the industry refer to the PMAD as the MAPE, although they compute this volume weighted MAPE. Difference between MAPE and WMAPE is explained in Calculating Demand Forecast Accuracy
Applications of forecasting
Forecasting has application in many situations:
- Supply chain management
- Weather forecasting, Flood forecasting and Meteorology
- Transport planning and Transportation forecasting
- Economic forecasting
- Technology forecasting
- Earthquake prediction
- Land use forecasting
- Product forecasting
- Player and team performance in sports
- Telecommunications forecasting
- Forecasting Principles: "Evidence-based forecasting"
- [http://http://www.itl.nist.gov/div898/handbook/pmc/section4/pmc4.htm Introduction to Time series Analysis (Engineering Statistics Handbook)] - A practical guide to Time series analysis and forecasting
- Time Series Analysis
- Applied Forecasting: news on forecasting
- Global Forecasting with IFs
- Turchin, P., 2007. Scientific Prediction in Historical Sociology. History & Mathematics: Historical Dynamics and Development of Complex Societies. Moscow: KomKniga. ISBN 5484010020
forecast in Simple English: Forecasting
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