Forecasting
Forecasting is the process of
estimation in unknown situations.Prediction is a similar, but more general term. Both can refer to estimation oftime series , crosssectional or longitudinal data. Usage can differ between areas of application: for example inhydrology , the terms "forecast" and "forecasting" are sometimes reserved for estimates of values at certain specificfuture 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 anduncertainty are central to forecasting and prediction. Forecasting is used in the practice ofCustomer 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 timeseries data.
Categories of forecasting methods
Time series methods
Time series methods use historical data as the basis of estimating future outcomes.*
Moving average
*Exponential smoothing
*Extrapolation
*Linear prediction
*Trend estimation
*Growth curve
*TopicsCausal / 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 usinglinear regression ornonlinear regression
*Autoregressive moving average (ARMA)
*Autoregressive integrated moving average (ARIMA):e.g.BoxJenkins
*Econometrics Judgmental methods
Judgmental forecasting methods incorporate intuitive judgements, opinions and
probability estimates.*
Composite forecasts
*Surveys
*Delphi method
*Scenario building
*Technology forecasting
*Forecast by analogy Other methods
*
Simulation
*Prediction market
*Probabilistic forecasting andEnsemble forecasting
*Reference class forecasting Forecasting accuracy
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:
{N}
Mean Absolute Percentage Error (MAPE)
$MAPE\; =\; frac\{sum\_\{t=1\}^N\; frac\{E\_t\}\{Y\_t\}\{N\}$

Percent Mean Absolute Deviation (PMAD)
$PMAD\; =\; frac\{sum\_\{t=1\}^\{N\}\; E\_t\{sum\_\{t=1\}^\{N\}\; Y\_t$
Mean squared error (MSE)
$MSE\; =\; frac\{sum\_\{t=1\}^N\; \{E\_t^2\{N\}$

Root Mean squared error (RMSE)
$RMSE\; =\; sqrt\{frac\{sum\_\{t=1\}^N\; \{E\_t^2\{N$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 See also
*
Forecast error
*Calculating Demand Forecast Accuracy
*Predictability
*Prediction interval , similar toconfidence interval Applications of forecasting
Forecasting has application in many situations:
*
Supply chain management
*Weather forecasting ,Flood forecasting andMeteorology
*Transport planning andTransportation forecasting
*Economic forecasting
*Technology forecasting
*Earthquake prediction
*Land use forecasting
*Product forecasting
*Player and team performance in sports
*Telecommunications forecasting
*Political Forecasting ee also
*Calculating Demand Forecast Accuracy
*CPFR
*Foresight (future studies)
*Futures studies
*Futurology
*Global Prescience
*Optimism bias
*Planning
*Prediction
*Reference class forecasting
*Strategic foresight
*Technology forecasting References
*cite book
author =Armstrong, J. Scott (ed.)
title= "Principles of forecasting: a handbook for researchers and practitioners
date= 2001
publisher= Kluwer Academic Publishers
location= Norwell, Massachusetts
language= English
id= ISBN 0792379306*cite book
author=Geisser, Seymour
authorlink =Seymour Geisser
title = Predictive Inference: An Introduction
date = 1 June 1993
publisher = Chapman & Hall, CRC Press
language = English
id = ISBN 0412034719*cite book
author=Makridakis, Spyros
coauthors=Wheelwright, Steven; [http://www.robhyndman.info Hyndman, Rob J]
title= [http://www.robhyndman.info/forecasting/ Forecasting: methods and applications]
date=1998
publisher = John Wiley & Sons
location = New York
language = English
id= ISBN 0471532339*cite book
author = Kress, George J.
coauthors= Snyder, John
title= "Forecasting and market analysis techniques: a practical approach
date= 30 May 1994
publisher= Quorum Books
location= Westport, Connecticut, London
language= English
id= ISBN 089930835X*cite book
author=Rescher, Nicholas
authorlink =Nicholas Rescher
title = Predicting the future: An introduction to the theory of forecasting
date = 1998
publisher = State University of New York Press
language = English
id = ISBN 0791435539*Turchin, P., 2007. Scientific Prediction in Historical Sociology. [http://edurss.ru/cgibin/db.pl?cp=&page=Book&id=53185&lang=en&blang=en&list=Found History & Mathematics: Historical Dynamics and Development of Complex Societies.] Moscow: KomKniga. ISBN 5484010020
External links
* [http://www.forecastingprinciples.com Forecasting Principles: "Evidencebased forecasting"]
* [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
* [http://www.statsoft.com/textbook/sttimser.html Time Series Analysis]
* [http://www.appliedforecasting.com Applied Forecasting: news on forecasting]
* [http://www.ifs.du.edu Global Forecasting with IFs]
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