### Table 1. Patterns in the theoretical ACF and PACF of stationary time series.

"... In PAGE 12: ... PACF can be obtained by Yule-Walker equation [23]. Table1 represents the patterns in the theoretical ACF and PACF of stationary time series, which is utilized to determine the order of model. ... In PAGE 13: ...igure 5. Analysis of ACF and PACF patterns: (a) ACF; (b) PACF. (a) (b) Taking the IMF1 in Figure 4 for example, its ACF and PACF are presented in Figure 5. According to Table1 , we choose the model AR(6) . In the same way, models are chosen for all the IMFs and the final residue series.... ..."

### Table 1: Average Scores for Stationary and Time- Varying AEPTFs for the Subband (SUB) and Wide- band (WB) Approaches

1996

"... In PAGE 4: ... The pre- sentation level was maintained at around 70 dB SPL and the subjects rated the sound quality of the pro- cessed sounds on a scale from 1 (poor) to 5 (excellent). Table1 shows average scores for the wideband and subband NLMS approaches under di erent conditions; the results indicate that the subband approach per- forms in a similar fashion to the wideband approach with a reduction of 75 % in complexity. It should be noted that convergence plots (Figure 6) showed faster convergence but higher normalized steady-state error for the subband case when compared to the wideband implementation.... ..."

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### Table 1 n PC PCS PL PLS MW MWS

2003

"... In PAGE 16: ... Table1 . Integrated mean squared errors (multiplied by 1000) of median estimates for simulated locally stationary time series (15): piecewise constant (PC), piecewise constant, smoothed (PCS), piecewise linear (PL), piecewise linear, smoothed (PLS), moving window (MW), moving window, smoothed (MWS).... ..."

### TABLE 6: Crowding out of reciprocity through incentive contracts

### Table 3: FIML estimation of the system of equations (2-4) for Program Participation, Condom Use and Prices

"... In PAGE 14: ... Condom use in this specification shows a positive but non-significant effect consistent with our belief that these estimates may be biased upward because of unobserved heterogeneity given the strong preferences among clients against using condoms. Table3 reports the results from the FIML estimates of the system of equations (2), (3) and (4)9. The flip chart equation estimates are reported in table 3A.... In PAGE 14: ... The reason for this is unclear, but one possibility is that brothels with a high proportion of married sex workers are run by madams who may have been more resistant to allowing access to peer educators. Table3 B provides FIML estimates of equation (3) determining condom use. The most important effect to note here is the impact of seeing the flip-chart which increases the probability of using condoms by 28 per cent, at a 1% level of significance.... In PAGE 15: ... Once again we see that sterilization and number of children has no impact on condom use suggesting that condoms are not used as contraceptives but as a STD/HIV prevention mechanism. Finally, Table3 C reports FIML estimates of the determinants of log prices. First, note the negative and highly significant impact of condom use on prices.... ..."

### Table 2. Summary of the Crowding Factors and Quenching Efficiencies of the Fluorophores in the Presence of TNTa

"... In PAGE 4: ... Using the diffusion coefficients of the fluorophores previously determined in this laboratory and estimating the radius of TNT to be about 1 nm, k0 was calculated, and the results are shown in Table 1. The two rate constants, kq and ko, are related by the quenching efficiency, fq: Values of the quenching efficiency are presented in Table2 where it can be ascertained that whereas [Ru- (bpy)3]2+ had the lowest value at 0.014, the value maximized at 0.... ..."

### Table 6. Estimates of Take-Up and Crowd-Out Associated with SCHIP Expansions Under Different Assumptions

2002

"... In PAGE 20: ... Nonetheless, under certain assumptions we can construct several measures of take-up and crowd-out associated with the SCHIP expansions and the associated changes in the number of children with particular coverage types. Table6 displays these estimates. The ... In PAGE 22: ... The largest of these estimates corresponds to a total of 76,000 children. In the second panel of Table6 we adjust the take-up and crowd-out estimates for the possibility that the increase in non-group private insurance associated with the SCHIP eligibility expansions actually represents an increase in public coverage. To calculate an adjusted take-up rate among the income eligible we sum the effect of public eligibility on public coverage with the estimated effect on non-group.... ..."

### Table 6: Full Sample Estimates of Take-Up and Crowd-Out

2005

"... In PAGE 23: ... Finally, including more years of data has the secondary effect of leading to an improvement in the precision of the estimates. The results from the 1987-1995 sample are summarized in Table6 for all children and for children with family incomes below 300 percent of the poverty line. As with the 1987-1992 data, the results do not differ substantially for the restricted and unrestricted samples.... ..."

### Table 6: FGN Whittle H estimates for 5 disjoint subsets of 128 points, for X(100).

1998

"... In PAGE 6: ... We divide X(100) for each trace into ve subsets of 128 points each, and run the FGN Whittle estimator on each subset. Table6 shows H(100) i ; 1 i 5 for each subset, along with H(100) = 1 5 P5 i=1 H(100) i and the estimate of H from the entire trace. For some traces, the variation of the H esti- mates is quite large.... In PAGE 6: ... In [12] it is shown that for stationary time series, H(100) has the same asymptotic distribution as H(100); thus, in cases where the entire trace is well-modeled with a constant H, we expect that H(100) H(100). Consid- ering Table6 , we nd that in cases where the H(100) i apos;s do not uctuate dramatically, this property holds quite well. In par- ticular, we conclude that UIC-1, UIC-4, UCD-4, SIT-1, and SIT-2 are reasonably well-modeled with constant H as de- termined by the FGN Whittle estimator on the entire trace.... ..."

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### TABLE 2.6. PRIVATE INVESTMENT, CORRUPTION, AND CROWDING OUT: REGIONAL RESULTS Independent variable Full LAC ASIA SSAFR ECA MENA

2001