B. Extremes, Extrapolation, And Surprise
Risk AnalysisPublished 1 February 1999Open access
Nicholas C. Matalas, Vicki M. Bier
Citations9
SJR quartileQ1
SJR score0.87
SNIP1.51
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
Abstract
has very complex methods for estimating confidence intervals around the esti-
Keywords
Social SciencesEngineering
Risk AnalysisOn The Quantitative Definition of Risk
3,047 Citations1981Stanley Kaplan, B. John Garrick
Annual Review of EnergyPhilosophical Basis for Risk Analysis
170 Citations1976Chauncey Starr, Richard Rudman +1 more
Water Resources ResearchRisk‐based analysis of extreme events
44 Citations1988Per‐Ola Karlsson, Yacov Y. Haimes
Water Resources ResearchProbability distributions and their partitioning
35 Citations1988Per‐Ola Karlsson, Yacov Y. Haimes
This paper analyzes how conditional expectations are sensitive to variations in partitioning and suggests which type of distribution function best represents the random process.
Management ScienceIndependence and Calibration in Decision Analysis
34 Citations1977J. Michael Harrison
International Journal of Water Resources DevelopmentSurprise in water‐resource design
13 Citations1984Myron B. Fiering, J. Kindler