TY - JOUR

T1 - A Bayesian approach to analyzing uncertainty among flood frequency models

AU - Wood, Eric F.

AU - Rodríguez‐Iturbe, Ignacio

PY - 1975/1/1

Y1 - 1975/1/1

N2 - The statistical uncertainty resulting from the lack of knowledge of which model represents a given stochastic process is analyzed. This analysis of model uncertainty leads to a composite Bayesian distribution. The composite Bayesian distribution is a linear model of the individual Bayesian probability distributions of the individual models, weighted by the posterior probability that a particular model is the true model. The composite Bayesian probability model accounts for all sources of statistical uncertainty, both parameter uncertainty and model uncertainty. This model is the one that should be used in applied problems of decision analysis, for it best represents the knowledge, or lack of it, to the decision maker about future events of the process.

AB - The statistical uncertainty resulting from the lack of knowledge of which model represents a given stochastic process is analyzed. This analysis of model uncertainty leads to a composite Bayesian distribution. The composite Bayesian distribution is a linear model of the individual Bayesian probability distributions of the individual models, weighted by the posterior probability that a particular model is the true model. The composite Bayesian probability model accounts for all sources of statistical uncertainty, both parameter uncertainty and model uncertainty. This model is the one that should be used in applied problems of decision analysis, for it best represents the knowledge, or lack of it, to the decision maker about future events of the process.

UR - http://www.scopus.com/inward/record.url?scp=0016647131&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0016647131&partnerID=8YFLogxK

U2 - 10.1029/WR011i006p00839

DO - 10.1029/WR011i006p00839

M3 - Article

AN - SCOPUS:0016647131

VL - 11

SP - 839

EP - 843

JO - Water Resources Research

JF - Water Resources Research

SN - 0043-1397

IS - 6

ER -