Fusion of detection probabilities and comparison of multisensor systems

Krzysztofowicz, Roman; Long, Dou

doi:10.1109/21.57281

Cited by 47 publications

(12 citation statements)

References 15 publications

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“…To the extent that there is miscalibration (e.g., conditional or unconditional biases) the score reflects penalties endured by decision-makers who take the forecasts at face value. It is sometimes assumed in this context that the forecast user can and will recalibrate forecasts based on past performance of those forecasts (Krzysztofowicz, 1992;Krzysztofowicz & Long, 1990), a process which is equivalent to the bias corrections yielding the dashed curves in Figure 3. However, it is arguably unreasonable to expect realworld decision-makers to perform this task when it is the forecaster or forecasting agency who should have the information required to correct forecast miscalibration.…”

Section: Discussionmentioning

confidence: 99%

A skill score based on economic value for probability forecasts

Wilks

2001

Meteorological Applications

122

134

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An approach to evaluating probability forecasts for dichotomous events, based on their economic value over all possible cost/loss ratio decision problems, is proposed. The resulting Value Score (VS) curve shows non‐dimensionalised relative economic value as a function of the cost/loss ratios for different decision‐makers, over their full meaningful range. The VS curve is similar in terms of computational mechanics and graphical display to the Relative Operating Characteristic (ROC) curve, but the ROC curve is shown to be insensitive to either conditional or unconditional biases and thus to reflect potential rather than actual skill. The possibility of collapsing the VS curve into a single scalar score is addressed, and it is shown that the results can depend very strongly on the assumed distribution of cost/loss ratios in the community of forecast users. Copyright © 2001 Royal Meteorological Society

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Section: Discussionmentioning

confidence: 99%

A skill score based on economic value for probability forecasts

Wilks

2001

Meteorological Applications

122

134

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“…In this graph, the probability forecast is not calibrated, as the VS curve lies beneath zero for some cost/loss ratios. Krzysztofowicz (1992) and Krzysztofowicz and Long (1990) showed that recalibration (i.e., relabeling) of such forecasts will not change the refinement but can improve the value score over the entire range of cost/loss ratios, which again is evidence that forecast skill would affect the forecast value. For the ROC curve, however, Wilks (2001) demonstrated that even with such recalibration, the recalibrated ROC curve will not change.…”

Section: Evaluation Of Forecast Valuementioning

confidence: 96%

Forecasting Binary Outcomes

Lahiri

Liu

2013

Handbook of Economic Forecasting

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“…In other words, it is the arrangement of algorithms into a processing architecture that distinguishes fusion from other data analysis systems. Examples of such schemes are presented in [29][30][31][32][33][34][35] and many others. All of the architectures presented in these papers and books could be formally specified using our formal approach.…”

Section: Other Conceptualizations Of Information Fusionmentioning

confidence: 99%