### Table 2. 2MASS Non-Parametric Luminosity Functions

12

"... In PAGE 7: ... The luminosity function estimation software was tested using synthetic catalogs drawn from a Poisson spatial distribution of galaxies selected from Schechter luminosity functions. The SWML binned luminosity functions are presented in Table2 and the Schechter function model luminosity functions are presented in Table 3. Figure 3 shows luminosity functions for the full sample, the early-type galaxies and the late-type galaxies using the two di erent estimation methods.... ..."

### Table 4: Non-parametric estimation without a kernel. a: Without Heteroskedasticity. T serial

1997

"... In PAGE 43: ...o zero, then ut is homoskedastic (condition (2.31) is satisfied). When the BD filter is used, the product Vt displays a fairly simple pattern of serial correlation pattern, whereas the BHP filter generates relatively complicated serial correlation. Table4 reports the confidence intervals obtained for a test of the null hypothesis of no covariance between ut and xt . The R95 estimator is compared with the QS estimator of Andrews (1991) without prewhitening.... ..."

Cited by 4

### Table 4 Non-Parametric Estimates of the Variance of the Innovation in the R.W. Component as a Ratio to the Total Variance of the Series (V)

"... In PAGE 13: ....[ ] [. [ / ]]/ = + 075 1 12 (13) Estimates of V k for alternative values of k are reported in Table4 for the series under consideration. The results are broadly consistent with those derived using the Yule-Walker equations.... ..."

### Table 5: Pooled Sample: Non-Parametric and Parametric Tests

1999

"... In PAGE 4: ...Tables Table 1: Model 12TE: Estimation Outcomes Table 2: Pooled Sample (37 MUNIs, 39 ENEL): SFM3 Estimation Outcomes Table 3: MUNIs and their ENEL Peers (SFM3): Winners/Losers Table 4: MUNI/ENEL Efficiency Comparison (SFM3): Statistics of Interest Table5 : Pooled Sample: Non-Parametric and Parametric Tests... ..."

Cited by 1

### Table 2: Average and standard deviation of test set log-loss of the networks learned with and without using the con- straints from the non-parametric bootstrap estimation.

1999

"... In PAGE 9: ... In Table 1 we report the score of the networks induced by this procedure. In Table2 we re- port the error from the generating distribution (measured in terms of log-likelihood assigned to test data) for the same networks. These results show that for small training sets we can find slightly better scoring networks using the constraints generated by the bootstrap.... ..."

Cited by 36

### Table 2: Average and standard deviation of test set log-loss of the networks learned with and without using the con- straints from the non-parametric bootstrap estimation.

"... In PAGE 9: ... In Table 1 we report the score of the networks induced by this procedure. In Table2 we re- port the error from the generating distribution (measured in terms of log-likelihood assigned to test data) for the same networks. These results show that for small training sets we can find slightly better scoring networks using the constraints generated by the bootstrap.... ..."

### Table 2: Average and standard deviation of test set log-loss of the networks learned with and without using the con- straints from the non-parametric bootstrap estimation.

"... In PAGE 9: ... In Table 1 we report the score of the networks induced by this procedure. In Table2 we re- port the error from the generating distribution (measured in terms of log-likelihood assigned to test data) for the same networks. These results show that for small training sets we can find slightly better scoring networks using the constraints generated by the bootstrap.... ..."

### Table 2.14: Characteristics of Density Estimation Approach Non-Parametric Approach Gaussian GMM

2004

### Table 3. Two-Way Non-Parametric ANOVA Test Results

"... In PAGE 9: ...001) for all considered aspects of the voice with the synthesized voice having lower ratings than the real voice. Interaction Effect between Character and Voice We found no significant interaction effect between Character and Voice for all statements (as can be seen in Table3 ) . Though, it should be noticed that statement 9, concerning the story understanding trough the voice communication mean, has an interaction effect value (p = 0.... In PAGE 12: ... This table displays the data organized by independent variable and video. Table3 reveals the results obtained through an analysis of variance. The statistical test used is a two-way non-parametric analysis of variance described in [12].... ..."

### Table 3. Two-Way Non-Parametric ANOVA Test Results

"... In PAGE 7: ...plays the data organized by independent variable and video. Table3 reveals the results obtained through an analysis of variance. The statistical test used is a two-way non-parametric analysis of variance described in [12].... In PAGE 8: ...3 Table 2. Percentage of Positive, Neutral and Negative ratings Gestures - As shown in Table3 , there are no significant differences in the evaluation of gestures when varying the nature of the voice. Voice - There is a high significant difference (p lt; 0.... In PAGE 8: ...001) for all considered aspects of the voice with the synthesized voice having lower ratings than the real voice. Interaction Effect between Character and Voice As can be seen in Table3 there is no significant interaction effect between Character and Voice for all statements. Though, it should be noticed that state- ment 9, concerning the story understanding trough the voice communication... ..."