### Table 1. U.S. Meat Demand Models: Thep-values for Full-System Misspecification Tests

### Table 1 Implementation complexity of programming models using HAMSTER Programming model No. of lines No. of API calls Lines/call Platform

### Table 2. U.S. Meat Demand Models: Thep-values for Equation-by-Equation System Misspe- cification Tests a

"... In PAGE 12: ... Table2 . Continued Model C Model D Item Beef Pork Chicken Beef Pork Chicken Individual Tests Normality Functional Form: RESET2 KG2 Heteroskedasticity:b Static Beef RESET2 Pork Chicken Static Beef WHITE Pork Chicken Dynamic Beef Pork Chicken Autocorrelation Parameter Stability: Variance Mean Joint Tests Overall Mean Test Parameter Stability Functional Form Autocorrelation Overall Variance Test:b Beef Pork Chicken Parameter Stability: Beef Pork Chicken Static Heteroskedasticity: Beef Pork Chicken Dynamic Heteroskedasticity: Beef Pork Chicken 0.... ..."

### Table 6. Frequency of Scale Efficient firmsa

in IMPRESSUM

2006

"... In PAGE 21: ...and Wilson (2002). lt;Please, insert Table6 about here gt; Table 6 presents absolute and relative number of scale efficient firms, that is, firms for which Test 1 is not rejected. We first notice that the total number of firms has been decreasing over time.... In PAGE 21: ...and Wilson (2002). lt;Please, insert Table 6 about here gt; Table6 presents absolute and relative number of scale efficient firms, that is, firms for which Test 1 is not rejected. We first notice that the total number of firms has been decreasing over time.... In PAGE 21: ... Most amazingly, all large firms are scale efficient in all observed periods. The increase in the share of scale efficient firms, which we noticed in Table6 mostly stems from a jump in the share of small-scale efficient firms and their large number in comparison to middle firms, whose share plummeted. After the third quarter of 2003 the share of middle firms remained virtually the same, while the share of small firms dropped.... ..."

### Table 5. Size of the Sample of Compounds Classified to Be Active by Each Method as a Percentage of the Whole Test Set for Each Target

2005

"... In PAGE 4: ... Although the study of structure-activity relationships is not within the scope of this paper, we speculate that ligands of DH and AE contain a subset of compounds with particular features, such as steroids, which render them more easily distinguishable from the bulk of nonactives. Because, in this study, the sample size is not kept fixed but allowed to vary according to the classification, high enrichment factors can be achieved with a high number of false negatives if the sample size is small ( Table5 ). For example, TV, yielding high enrichment factors, predicts in many cases a smaller number of compounds to be active than do other methods (Table 5).... In PAGE 4: ... Because, in this study, the sample size is not kept fixed but allowed to vary according to the classification, high enrichment factors can be achieved with a high number of false negatives if the sample size is small (Table 5). For example, TV, yielding high enrichment factors, predicts in many cases a smaller number of compounds to be active than do other methods ( Table5 ). For this reason, recall values were also calculated, which give the percentage of all actives which have been retrieved (Figure 1b).... ..."

### Table 1 Commands at Each Level of Abstraction in LaSRS++

"... In PAGE 4: ... The number of commands is small compared to the number of data items. Table1 lists commands at each abstraction level. The listed commands constitute the minimal interface for operating a given abstraction level.... ..."

### Table 5 Adjusteda odds ratios from logistic regression models predicting Model 1 (dieting in past year) and Model 2 (binge eating)

2002

"... In PAGE 7: ...01). Table5 presents the adjusted odds ratios from logistic regression models predicting dieting in the past year (Model 1) and ever binge eating (Model 2). Both models adjusted for effects of education and BMI.... ..."

### Table 4: The best ve models for eachgiven number of input variables

1999

"... In PAGE 11: ... Consequently, one can consider the model that has the maximum R 2 p value an optimum model. Table4 shows the ve best models that maximize R 2 p for eachgiven number of inputs, 3 r 9. The rst column of Table 4 shows the identi cation numbers of the examined models.... In PAGE 11: ... Table 4 shows the ve best models that maximize R 2 p for eachgiven number of inputs, 3 r 9. The rst column of Table4 shows the identi cation numbers of the examined models. The best models for eachgiven r (3 r 9) are retained for further comparison (models 1, 6, 11, 16, 21, 26 and 31).... ..."

Cited by 4

### Table 1 shows the results of the study. For each model, the optimal parameters and a measure of the model apos;s average error are presented. Average error provides a single measure of performance that can be used to compare models, it is defined below.

"... In PAGE 3: ... error: 32.62% Table1 : User model parameter estimation results DISCUSSION The average errors of models 2-4 is significantly less than that for model 1, with the most sophisticated (model 4) yielding an improvement of 9.85 and 15.... ..."