### Table 1: Quadratic or Nonparametric?

2001

"... In PAGE 8: ... The squared L2 risks of the estimators are computed based on 100 replications. The numbers in the parentheses in Table1 are the corresponding standard errors. Quadratic regression works much better than the nonparametric alternatives for the rst two cases, but becomes much worse for the latter two due to lack of exibility.... ..."

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### Table 3 shows the errors of nonparametric regression. The

2000

"... In PAGE 6: ...Figure 5: Rule #28Finger 4#29 Figure 6: Rule #28Finger 5#29 Figure 7: Rule #28Finger 12#29 Figure 8: Rule #28Finger 15#29 Figure 9: Rule #28Finger 21#29 Figure 10: Rule #28Finger 25#29 Table3 : Error #28Shiritori#29 slice err. slice err.... ..."

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### Table A2: Nonparametric (Kernel) Regressions

### Table 4: Valuing American put options using nonparametric regression

"... In PAGE 10: ... For details about the smoothing spline, see the help file of Matlab. The results are in Table4 and Figure 2. Table 4: Valuing American put options using nonparametric regression ... ..."

### Table 5 Multiple regression of differences between bootstrap and Bayes classifiers (study II)

2007

"... In PAGE 13: ... However, for the smallest level of separation the aggregate classifier tends to perform slightly worse. As before a regression analysis was performed to establish the relation between the difference in performance of the two classifiers and the design factors ( Table5 ). As can be seen, using the parametric bootstrap (compared to the nonparametric) improves the relative performance of the aggregate classifier.... ..."

### TABLE 2 MULTIPLE REGRESSION

### TABLE 3 MULTIPLE REGRESSION

"... In PAGE 80: ...3.49) were rated as important by respondents. See Table 3. TABLE3 (continued) IMPORTANCE OF ACADEMIC QUALIFICATIONS TO HIRING DECISION MEAN RESPONSES ACADEMIC QUALIFICATIONS Teaching Overall R-O T-O AACSB NONACC Perceived willingness to accept quot;heavy quot; prep load 2.95 1.... ..."

### Table 1: Nonparametric Lag Selection for Lynx Data

2000

"... In PAGE 14: ... We follow the suggested procedure of the last section and use only the CAF P E1 and the CAF P E2a criteria and for reasons of comparison, the linear Schwarz criterion ARSC. Table1 summarizes the results for the lynx data. Except for the CAF P E1 criterion all criteria include lag 1 and 2 in their selection.... In PAGE 14: ... Recalling the results of the previous section, these lags for the CAF P E2a may be due to over tting. To decide whether the more parsimonious model is su cient, we investigated the residuals of all suggested models using the bandwidths of Table1 and conclude that lags 1 and 2 are su cient. A plot of the estimated regression function on a relevant grid is shown in Figure 5.... In PAGE 15: ...and 3 using AF P E1 while Yao and Tong (1994) found lags 1, 3 and 6 using cross-validation. Insert Table1 about here Applying our methods to daily exchange rate data poses a di erent challenge. While there are plenty of data (3212 observations), this bene t is compromised as the data is known to be highly dependent (although only weakly correlated) and therefore asymptotics kick in very slowly.... ..."

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### Table 10: Pinball loss comparison between the nonparametric quantile regression without (npqr) and with (npqrm) monotonicity constraints.

2006

"... In PAGE 27: ... Note that on the engines data set the monotonicity constraint is not perfectly satisfied. Table10 shows the average pinball loss comparison between the nonparametric quantile regression without (npqr) and with (npqrm) monotonicity constraints. See above for the notation of the table.... ..."

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