The effect of learning on the assessment of subjective probability distributions

1971 ◽  
Vol 6 (3) ◽  
pp. 304-315 ◽  
Author(s):  
Carl-Axel S. Staël von Holstein
Keyword(s):  
Subjective Probability ◽  
Probability Distributions

A Comparison of Subjective and Historical Crop Yield Probability Distributions

1992 ◽  
Vol 24 (2) ◽  
pp. 23-32 ◽  
Author(s):  
James W. Pease
Keyword(s):  
Crop Yield ◽  
Subjective Probability ◽  
Crop Yields ◽  
Probability Distributions ◽  
Geographical Location ◽  
Subjective Expectations ◽  
Grain Farms ◽  
Western Kentucky ◽  
Relative Variability

AbstractForecast distributions based on historical yields and subjective expectations for 1987 expected crop yields were compared for 90 Western Kentucky grain farms. Different subjective probability elicitation techniques were also compared. In many individual cases, results indicate large differences between subjective and empirical moments. Overall, farmer expectations for 1987 corn yields were below those predicted from their past yields, while soybean expectations were above the historical forecast. Geographical location plays a larger role than crop in comparisons of relative variability of yield. Neither elicitation technique nor manager characteristics have significant effects on the comparisons of the forecasts.

Seismic hazard sensitivity analysis: A multi-parameter approach

1991 ◽  
Vol 81 (3) ◽  
pp. 796-817
Author(s):  
Nitzan Rabinowitz ◽  
David M. Steinberg
Keyword(s):  
Sensitivity Analysis ◽  
Seismic Hazard ◽  
Subjective Probability ◽  
Probability Distributions ◽  
Input Parameter ◽  
The Other ◽  
Probabilistic Assessment ◽  
Input Parameters ◽  
Parameter Approach

Abstract We propose a novel multi-parameter approach for conducting seismic hazard sensitivity analysis. This approach allows one to assess the importance of each input parameter at a variety of settings of the other input parameters and thus provides a much richer picture than standard analyses, which assess each input parameter only at the default settings of the other parameters. We illustrate our method with a sensitivity analysis of seismic hazard for Jerusalem. In this example, we find several input parameters whose importance depends critically on the settings of other input parameters. This phenomenon, which cannot be detected by a standard sensitivity analysis, is easily diagnosed by our method. The multi-parameter approach can also be used in the context of a probabilistic assessment of seismic hazard that incorporates subjective probability distributions for the input parameters.

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