Title :
Uncertainties in modeling low probability/high consequence events: application to population projections and models of sea-level rise
Author :
Shlyakhter, Alexander I. ; Kammen, Daniel M.
Author_Institution :
Dept. of Phys., Harvard Univ., Cambridge, MA, USA
Abstract :
The authors present a simple method for estimating uncertainty in modeling and forecasts based on an analysis of errors in old measurements and projections. They develop an empirical method of quantifying the uncertainty in a time-series of historical forecasts for which the actual values are now known. Probabilities of large deviations are parametrized by an exponential function with one free parameter. This formulation is illustrated by quantifying uncertainties in national population projections and by estimating the probability of extreme sea-level rise resulting from global warming
Keywords :
demography; forecasting theory; probability; statistical analysis; time series; uncertainty handling; empirical method; exponential function; extreme sea-level rise; forecasts; global warming; historical forecasts; national population projections; old measurements; population projections; time-series; uncertainty; Current measurement; Data analysis; Demand forecasting; Error analysis; Fasteners; Gaussian distribution; Global warming; Predictive models; Probability distribution; Uncertainty;
Conference_Titel :
Uncertainty Modeling and Analysis, 1993. Proceedings., Second International Symposium on
Conference_Location :
College Park, MD
Print_ISBN :
0-8186-3850-8
DOI :
10.1109/ISUMA.1993.366761
