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Combining forecasts: A review and annotated bibliography
Abstract Considerable literature has accumulated over the years regarding the combination of forecasts. The primary conclusion of this line of research is that forecast accuracy can be substantiallyExpand
Making Hard Decisions: An Introduction to Decision Analysis
This text involves readers in real-world decisions from personal, federal, corporate and environmental areas. Readers should learn how to use the tools of decision analysis including decision treeExpand
Combining Probability Distributions From Experts in Risk Analysis
This paper concerns the combination of experts' probability distributions in risk analysis, discussing a variety of combination methods and attempting to highlight the important conceptual andExpand
Correlations and Copulas for Decision and Risk Analysis
The construction of a probabilistic model is a key step in most decision and risk analyses. Typically this is done by defining a joint distribution in terms of marginal and conditional distributionsExpand
Making Hard Decisions with DecisionTools
This new version incorporates and implements the powerful DecisionTools+ by Palisade Corporation, the world's leading toolkit for risk and decision analysis. Expand
Making Hard Decisions
Some authors can irritate me with their approach to their presentation of their material. Here the author has used four footnote references at the end of Chapter 1, three referring to web sites andExpand
Combining Economic Forecasts
A method for combining forecasts may or may not account for dependence and differing precision among forecasts. In this article we test a variety of such methods in the context of combining forecastsExpand
Limits for the Precision and Value of Information from Dependent Sources
The results indicate that positive dependence among information sources can have a serious detrimental effect on the precision and value of the information and have implications for the acquisition and use of information in decision-making problems. Expand
Subjective Probability Assessment in Decision Analysis: Partition Dependence and Bias Toward the Ignorance Prior
This work shows that assessed probabilities are systematically biased toward a uniform distribution over all events into which the relevant state space happens to be partitioned, so that probabilities are "partition dependent" and related research on the "pruning bias" in fault-tree assessment is related. Expand
Assessing Dependence: Some Experimental Results
This work discusses two experimental studies that compare the accuracy of six different methods for assessing dependence, and concludes that direct estimation is more accurate than the other methods studied, is not prone to mathematically inconsistent responses (as are some other measures), and is judged to be less difficult than alternate methods. Expand