### Table 5.4: Possible situations and approaches when comparing a prior and a posterior value.

2006

### lable prior information, we derive the joint posterior distribution and summarize the estimation approach.

Cited by 1

### Table 1. Comparison with other approaches.

"... In PAGE 4: ... That is, in top-down writing using these systems, users cannot get the adequate feedback from the intermediate representation. We summarize the merits and demerits of these prior approaches and OFMR ( Table1 ). Prior approaches have both positive and negative effects, which in this case are complementary.... In PAGE 4: ... Prior approaches have both positive and negative effects, which in this case are complementary. In each point of view of Table1 , OFMR provides positive effect. Table 1.... ..."

### Table 1. Comparison with other approaches.

"... In PAGE 4: ... That is, in top-down writing using these systems, users cannot get the adequate feedback from the intermediate representation. We summarize the merits and demerits of these prior approaches and OFMR ( Table1 ). Prior approaches have both positive and negative effects, which in this case are complementary.... In PAGE 4: ... Prior approaches have both positive and negative effects, which in this case are complementary. In each point of view of Table1 , OFMR provides positive effect. Table 1.... ..."

### Table 3: Generalization on the MONK apos;s problems The generalization accuracy of the individual learning algorithms on the MONK apos;s problems and that of combining prior symbolic knowledge with machine learning is shown in Table 3. As anticipated, the generalization of a combined approach surpasses that of each approach individually.

1993

Cited by 25

### Table 10: Estimated values using acceptance sampling based on Weak simulation runs, with the strong prior as revised prior.

"... In PAGE 23: ... However, this would introduce dependency between the simulation runs, and the e ective number of observations in the sample would not increase correspondingly. As shown in Table10 12 only part of the original simulation runs are retained. The proportion retained ranged from 20:6% to 3:9% and corresponds to the average weight value, and depends on the di erence between the sampling and the target density.... In PAGE 24: ... However, this is because some of the observations are replicated. The apos;e ective apos; number of observations is comparable to the accepted observations in Table10 12. As shown in Table 13 15 the results using this approach are similar to the previous.... ..."

### Table 3. Stocking (trees/ha) of forest prior to harvesting

"... In PAGE 6: ...for details of this approach, see e.g. Vanclay 1994). Data for recruitment, upgrowth and mortality were derived from permanent sample plots in the study area (Septiana 2000; Table 2). Operational inventory data ( Table3 ) were used to initiate the model with stocking estimates for the original forest stand before logging. The TPTI approach is implemented as a diameter limit with trees over 50 (production forest) or 60 cm dbh (limited production forest) being harvested.... ..."

Cited by 1

### Table 4. Contrast per cent relative difference analysis (equation (9)) on a lesion by lesion basis in the lung field through comparison of the Non-Corrected and Corrected images. Results are shown for both approaches of applying the transformation in the raw data prior to the reconstruction process (LORs-Affine) as well as in the images and subsequently summing them together (gated- Frames) or integrating the elastic transformation parameters within the reconstruction process (Elastic Method 1).

2007

### Table 6. Per cent relative difference analysis (equation (9)) of the FWHM of the different size lung lesions along the Y-andZ-axes. Results are shown for both approaches of applying the transformation in the raw data prior to the reconstruction process (LORs-Affine) as well as in the images and subsequently summing them together (gated-Frames) or integrating the elastic transformation parameters within the reconstruction process (Elastic Method 1). Non- gated- LORs- Elastic Lesion

2007