### Table 6 Position of maxima of predicted elution profiles for the two factor model

1998

"... In PAGE 5: ... The elution and spectral parameters found are given in Tables 6 and 7, respectively. As can be seen from Table6 , at each level of d the algorithm appears to detect successfully the reactant and product without any interference from the intermediate. Note that the product should elute at datapoint 6 and the reactant at datapoint 10.... In PAGE 6: ... 7. These supplement the data in Table6 ; it is obvious that for d = 20 the first factor has, in fact, two clear maxima. Interestingly, the intermediate is confused with the product and predicted as one factor, despite the difference in both spectral characteristics and elution profiles.... ..."

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### Table 5 Two-Factor Model With Common Unique Variances for the Cars Paired-Comparisons Data

"... In PAGE 15: ...df H11005 8, p H11005 .18). Thus, the two-factor model gives the most parsimonious representation for these data. We provide in Table5 the parameter estimates and standard errors for this two-factor model. The ordering of the mean utilities changes little for the different covariance structures.... In PAGE 15: ... Thus, the estimated means for the two-factor model given in Table 5 are very similar to those estimated under the unrestricted model (see Table 3). Figure 3 provides a plot of the factor loadings reported in Table5 . Because, in this model, the variances of the unique errors are set equal to each other, the relative distances between the compact cars remain invariant when identifi- cation restrictions are changed.... ..."

### Table 5: France Two-Factor Model|Maximum Likelihood Estimates Variable MLE Asy. SE

"... In PAGE 26: ... Both of the measurement error matrices ( and ) are constructed to be diagonal|there are no correlated measurement errors. The MLEs appear in Table5 . Standard error estimates were computed using PROC CALIS of SAS version 6.... In PAGE 42: ...rance only. The survey was conducted in October 1988. n = 440. a If there is more than one index number, the rst one refers to the two factor model ( Table5 and the second one refers to the one factor model (Table 6). b All of the variables have been recoded to range from 0 to 1 so that the higher number represents... ..."

### Table 2: Results of Monte Carlo study Double-Decay two-factor model

1997

"... In PAGE 26: ... Therefore, we only consider two parameter con gurations in this part of the Monte Carlo study, both assuming weekly data and quot; = 0:30. The true parameter values are given in Table2 , along with the sample mean and standard deviations of the QML estimates over 500 Monte Carlo replications. As in Table 1, the results are encouraging for the QML estimator although small biases are noticeable in case I, especially for ^ 1 and ^ 1.... In PAGE 27: ... Apart from this minor and economically insigni cant problem, there is a close resemblance between Tables 1 and 2 with respect to the performance of the QML estimator. For example, the market prices of risk, 1 and 2, are estimated somewhat imprecisely in Table2 , but this is clearly caused by a \multicollinearity quot; problem since the asymptotic interest rate, R(1), is estimated very precisely. 7 Concluding remarks The Monte Carlo evidence presented in section 6 is strongly supportive of the QML- IEKF method as nite sample biases are virtually non-existent, and key model pa- rameters are estimated quite precisely (the risk premia being the usual exception).... ..."

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### Table 2. | Parameter Estimates: Two Factor Models 10 22 10 20 22 close to close, f ptg

"... In PAGE 13: ... Relaxing the restriction 22 = 0 provides an acceptable t. Table2 shows the parameter estimates, Wald-type standard deviations, and 95 percent con dence intervals... In PAGE 14: ... Such con dence intervals inherit the invariance properties of criterion di erence test, and, unlike intervals based on the Wald test, they can be quite asymmetric when the objective function surface is quite asymmetric in that particular parameter. As seen from the top portion of Table2 , the point estimates of the two factor model tted to the f ptg series appear reasonable, with all parameters save 10 quite statistically signi cant. The nding that a two factor stochastic volatility di usion model can adequately describe the marginal dynamics of a price movement series f ptg alone is consistent with the ndings of Melino and Turnbull (1990), Engle and Lee (1996), Gallant and Long (1997), among others.... In PAGE 14: ... However, as seen from the middle and bottom portions of Table 1, the two factor model has considerable problems accounting for either the marginal dynamics of the range series fdtg or the joint dynamics f pt; dtg. Also, in Table2 the point estimates are di erent depending upon whether the score generator for the marginal fdtg series or the joint f pt; dtg series is used. Taken all together, the evidence in Tables 1 and 2 suggest that the success in tting the marginal dynamics of the price movement series is misleading, and, in fact, the two factor model misses important aspects of the price dynamics.... ..."

### Table 7 Predicted spectral parameters for the two factor model. The design parameters are given in Table 1

1998

"... In PAGE 5: ... Note that the product should elute at datapoint 6 and the reactant at datapoint 10. Again, in Table7 , it appears that the two-component model produces good predictions of the spectrum ratios and ab- sorbance maxima at each level of d, although the peak ratio for the product (1.56) is lower at d = 20.... ..."

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### TABLE 3 Results of Fitting a Two-Factor SARV Model to Daily Returns

### TABLE 4 Results of Fitting a Two-Factor SARV Model to Daily Returns and Trading Volume

### Table 9: Parameter estimates of a two-factor square-root model with nonlinear risk premium

"... In PAGE 23: ... Stationarity is imposed on parameter estimates produced with the Kalman filter. The true parameters of the process and a summary of the estimation results are displayed in Table9 . We first examine the results for ML estimation.... ..."

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### Table 7. The factor matrix of two-factor model with Direct oblim rotation where removed items of the scale are presented on grey background. Pattern Matrix(a) Factor

2005

"... In PAGE 9: ...able 6. Eigenvalues and % of items variance accounted for 7 factors. ..................................33 Table7 . The factor matrix of two-factor model with Direct oblim rotation where removed items of the scale are presented on grey background.... In PAGE 45: ... The Direct oblim rotation was conducted with delta value 0 to sample 1, and only those items that were positively correlated with the other items and had factor loadings greater than 0.40 were taken into analysis ( Table7 ). The communalities of ... In PAGE 47: ...Table7 . Total of 14 items of the original NUEQ were removed based on the orthogonal and oblique factor analyses.... ..."