EconPapers    
Economics at your fingertips  
 

Forecast Uncertainty and Monte Carlo Simulation

Sam Sugiyama

Foresight: The International Journal of Applied Forecasting, 2007, issue 6, 29-37

Abstract: Sam Sugiyama has written a primer on the use of Monte Carlo Simulation to assess forecast error. His simple illustrative example and description of the steps in the MCS procedure provide a non-technical overview of this fascinating approach to the evaluation of uncertainty in forecasts. For regression modelers specifically, Sam shows how MCS can be used to develop more realistic prediction intervals than the theoretical PIs found in books and software. Copyright International Institute of Forecasters, 2007

Date: 2007
References: Add references at CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://foresight.forecasters.org/shop/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:for:ijafaa:y:2007:i:6:p:29-37

Access Statistics for this article

More articles in Foresight: The International Journal of Applied Forecasting from International Institute of Forecasters Contact information at EDIRC.
Bibliographic data for series maintained by Michael Gilliland ().

 
Page updated 2025-03-19
Handle: RePEc:for:ijafaa:y:2007:i:6:p:29-37