### Table 5. Value prediction statistics

"... In PAGE 14: ... This result shows that implementing VP to overlap only L1 misses is not profitable for SMT. Table5 shows important statistics for VP. Coverage is the ratio of the number of predictions over the number of L1 load misses.... ..."

### Table 6. Hypothesis testing statistics of predictions from the two competitive models

2002

"... In PAGE 10: ... The statistics from these three sets of median and variance tests are summarized in Table 6. Inspection of the P values of the statistical tests listed in Table6 reveals some differences. The P values that result from comparing either the prediction or the relative error between predictions to the corresponding observations are greater than 0.... ..."

### Table 5. Diebold-Mariano Statistics of Predictive Accuracy

"... In PAGE 22: ... In particular, Table 3 reports the relative rankings and Table 4 contains the criteria values. Finally, Table5 reports the pairwise model comparison statistics based on Diebold-Mariano predictive accuracy tests for all the commodities and their nearbies. Only the results from one step ahead and five step ahead forecasts are reported here, but the results for two to four step ahead forecasts are available upon request.... In PAGE 23: ... Tables 3.1 and 3.2 report the rankings of all models and the values univariate model selection criteria based on one-step amd five-step ahead forecasts. Table5 reports the results from DM test statistics. In all of these tables, only the results from the most recent nearby and most distant nearby futures contracts are reported, for the sake of brevity.... In PAGE 24: ... In other words, all models are useful for predicting the direction of price changes. Entries in Table5 are the Diebold-Mariano statistics. At 10% significance level, all DM statistics suggest accepting the null hypothesis (i.... ..."

### Table 3. Error statistics for predictive model on extended ASAP2

2006

"... In PAGE 10: ...he swarm intelligence inspired system. As can be seen from Fig. 10, greater errors occur between the average of the 20 replicas and predicted outcomes. This can also be seen from Table3 , where the average error rate figures become greater compared with Table 1. This again proves that the behaviour of the system has been altered when leaders are introduced.... ..."

Cited by 1

### Table 7: Overall perception model: Wald Statistics for predicting error

2006

"... In PAGE 19: ... No four-way interactions were tested. The ANOVA table for the overall fitted model is given in Table7 , and the model coefficients are given in Table 8. A large number of these factors proved highly significant.... ..."

Cited by 2

### Table 52 Statistics of the Prediction Errors and Actual Resource Values.

### Table I. Error statistics of predicted shapes for Bone 1.

2005

### Table II. Error statistics of predicted shapes for Bone 2.

2005

### Tables Table 1: Summary statistics of the predictions for the 30 tissues examined.

2007

### Table 1: Descriptive statistics and concomitant predictions (prediction number in brackets)

"... In PAGE 4: ...nitiative, or is it more or less equal? (Dykstra et al., 2004). The dependent variable, frequency of contact, was surveyed as: How often have you seen {name, description} over the past 12 months. This variable was recoded from seven to five categories, by merging the first two in order to avoid categories with too few cases ( Table1 ). The variables used, their associated predictions and descriptives are summarized in table 1.... In PAGE 4: ... The variables used, their associated predictions and descriptives are summarized in table 1. Multinomial logistic regression (MLR) was used to investigate the independent effects of the variables from Table1 on contact frequency (Hosmer and Lemeshow, 1989; Menard, 1995; Pampel, 2000). Multinomial logistic regression as statistical technique is relatively free of assumptions and statistically robust.... In PAGE 4: ... As event we selected maintaining frequent contact (a few times a week or daily) with a grandchild, with increasing distance. Results The descriptive statistics and predictions are summarized in Table1 . There were no significant differences between grandparents in distance to their grandchild (ANOVA: F(1, 827) = 1.... In PAGE 4: ...05). The effects for the variables were in the predicted direction of Table1 , however (Table 2, see Pollet et al., 2006).... In PAGE 8: ...05). These effects were in the predicted direction as described in Table1 . Age and sex of the grandchild as well as initiative of contact and marital status of the child, were not significant predictors of frequent contact as a function of distance (Wald tests; p gt; .... In PAGE 9: ... As in our previous paper (Pollet et al., 2006), we find support for the majority of predictions listed in Table1 , both in the logistic and Cox regression analysis (MLR: support for predictions: 2,5,6,8,9,11,12; Cox regression: support for predictions: 1,2,4,5,9,11). Relatedness proved marginally significant in the logistic regression, with unrelated individuals having less contact than related individuals.... In PAGE 9: ... These findings appear robust and in line with the paternity uncertainty hypothesis. The findings cannot be attributed to a wide variety of factors listed in Table1 . If the necessary conditions are met, namely measures against social desirability and adequate control variables, the study of contact frequencies between grandparents and grandchild allows testing evolutionary hypotheses, such as the paternity certainty hypothesis.... ..."