Download e-book for kindle: A Bayesian forecasting model: predicting U.S. male mortality by Pedroza C.

By Pedroza C.

ISBN-10: 3900051070

ISBN-13: 9783900051075

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Additional info for A Bayesian forecasting model: predicting U.S. male mortality (2006)(en)(21s)

Example text

B). 05, find H and d'. (a). Suppose d' = 1. 5? (b) Plot the ROC from these points on linear and z coordinates, and use the zROC to confirm the value of d'. 2, find d' from H and F and also fromp(c). Is there a pattern to the results? 9) and (. , do they imply the same value of d')! 6). If F is unchanged, what would H have to be to double the participant's sensitivity, according to detection theory? If H is unchanged, what would F have to be? Plot the ROCs implied by the following measures, on both linear and z coordinates: H2 - F2, ffA - FA, H/F2, tfTF.

The Yes-No Experiment: Sensitivity FIG. 3. 13 ROCs implied by p(c) on linear coordinates. 5). If we add the same number to each of these scores (without any transformation), the resulting scores correspond to another point on the ROC. 92). Simply using p(c} as a measure of performance thus makes a prediction about how much the false-alarm rate will go up if the hit rate increases, and it is different from the prediction of detection theory. Which Implied ROCs Are Correct? The validity of detection theory clearly depends on whether the ROCs implied by d' describe the changes that occur in H and F when response bias is manipulated.

3 and solve it for H: = F+[2p(c)-l] . 9 is a straight line of unit slope. Implied ROCs for p(c) are shown in Fig. 8. 6. The Yes-No Experiment: Sensitivity FIG. 3. 13 ROCs implied by p(c) on linear coordinates. 5). If we add the same number to each of these scores (without any transformation), the resulting scores correspond to another point on the ROC. 92). Simply using p(c} as a measure of performance thus makes a prediction about how much the false-alarm rate will go up if the hit rate increases, and it is different from the prediction of detection theory.

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A Bayesian forecasting model: predicting U.S. male mortality (2006)(en)(21s) by Pedroza C.


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