"... In PAGE 10: ... Using the upper estimate of (19), we get kf ? fNkH?1=2 C0((C2 X 2 n N d2 )1=2 + kf ? fN kH?1=2) ; Using the lower bound, one gets kf ? fNkH?1=2 C3(( C1 (J )2 X 2 n N d2 )1=2 ? kf ? fN kH?1=2) : Provided that N is small compared to N and neglecting kf ? fN kH?1=2, we see that N = f k : k = 1; : : : ; Ng (20) is probably a good choice (it minimizes the upper bound for kf ? fNkH?1=2). Table4 shows results for this kind of a posteriori analysis. In the rst experiment, we have used = (0:5; 1; 0:001) [ ([2 j1;j2;j1+j2 6 j1;j2) (N = 277) ; which is a slightly smaller subset of (0:5; 6; 0:001).... In PAGE 12: ... 0;j, j = 7; : : : ; 13, exactly two functions associated with opposite edges are included into 117. Looking at the numbers C(N) given in Table4 , there remains some doubt about the constant in the asymptotic O(N?5=2) estimate for rel N following from the results of section 2 (what we should expect is C(N) C, at least asymptotically). Possibly, our a posteriori selection rule outlined above needs some improvement (note that J = 19 in both tests).... ..."

"... In PAGE 9: ... In fact, this is a very unfavourable scenario: in typical applications for instance, font homogeneity constraints could bring a decisive improvement through the process- ing of a sequence of consecutive words: if we err on one word with probability p (p small), then the error rate on n words tends quickly to 0 when n grows. Table2 presents the recognition rates for 10pt fonts. The results show that the method is as accurate as ApOFIS, having regards to their respective requirements.... ..."

"... In PAGE 35: ...Identification and Screening of Hazards Draft 100-NR-1 Operable Unit Remediation Emergency Preparedness Hazards Assessment March 2000 3-2 Table3 -2. Hazards Screening for 116-N-3 Trench Inventory.... ..."

"... In PAGE 5: ... This means that the parameter at a0a106a9 a35 a19 , correspondingto the time constant of the system, is constant in all the rules, a18 a18a7a12a26 a28 a3 a18 a99 a26 a28a72a14a7a6a25a104a17a14 a19 a51a3 a78a36a14a30a29a30a29a30a29a31a14 a3 [3]. In the unconstrained FCRM case, these poles of the local dynamic models are almost identical to each other and to the pole of the original system (see, Table1 ), so this constraint has only little contribution to the resulted model. It can be seen in Table 1, that two of the regression models (1 and 3) have almost the... In PAGE 5: ... In the unconstrained FCRM case, these poles of the local dynamic models are almost identical to each other and to the pole of the original system (see, Table 1), so this constraint has only little contribution to the resulted model. It can be seen in Table1 , that two of the regression models (1 and 3) have almost the... In PAGE 6: ... As these models are forced to be different, the operating regions of these models will be also different, hence the fuzzy partition of the operating space will be more distinguishable. By using constraints, the resulted models have the same a18 a34a7a12a26 a28 parameters that are identical to the parameters of the original system that generated the data, a89 a29 a2 , (see, Table1 ). Moreover, because of the gains of the local models are forced to be different from each other, the operating regions of the LTI models are clearly separated, Figure 3.... ..."

"... In PAGE 11: ...he agreement of the modelled results with measurements (see section 4.3). Otherwise, it is always possible to replace the a posteriori emissions in the grid cells where their uncertainty is expected to be too large with the a priori emissions. Table3 lists the a priori and a posteriori emission rates for 54 major cities marked on our plots. Most of these estimates are obtained using bilinear interpolation between four grid cells closest to the city centre.... In PAGE 11: ... Nevertheless, we believe that such data are useful, particularly because they are rather easy to use for inter- comparison with similar results of other inverse modelling studies and emission inventories. In accordance to our results, the a priori emissions are probably overestimated (or underestimated) for half of the cities (27) listed in Table3 . However, the differences between the a priori and a posteriori emissions exceed the uncertainty range only for part of the cities (21), which are marked in bold in Table 3.... In PAGE 11: ... In accordance to our results, the a priori emissions are probably overestimated (or underestimated) for half of the cities (27) listed in Table 3. However, the differences between the a priori and a posteriori emissions exceed the uncertainty range only for part of the cities (21), which are marked in bold in Table3 . In particular, a statistically significant overestimation of a priori emission is found for Baghdad (a factor of 3.... ..."

"... In PAGE 30: ... MLEs and standard errors (SEs) for the parameters of both models appear in Table 2.19 The coor- dinating model estimates in Table2 use method two (beta approximation) to compute ^ P. Most of the parameters that have the same interpretation in both models have statistically indistinguish- able estimates.... In PAGE 36: ...be at least an equal of the House in determining postelection policy. Most of the D and R point estimates are greater than :5 (see Table2 ), which suggests that voters usually believe the President to have more weight in policy outcomes than does the House. Jimmy Carter running for reelection in 1980 is an exception (^ D;80 = :4), but the most striking case of anticipating a weak President is Bob Dole in 1996 (^ R;96 = :1).... In PAGE 42: ... Table2 shows D;76, D;92, R;80, and R;96 to have MLEs equal to 1:0, on the conceptual boundary of the parameter space. The boundary is not a \natural quot; boundary (Moran 1971b) for the probabil- ity model: LC is a proper (although meaningless) likelihood for values of D, D, or R outside [0; 1].... In PAGE 42: ... For the coordinating voting model, the hypothesis D;76 = D;92 = R;80 = R;96 = 1 implies a distribution that is a mixture of 16 censored distributions. I use a bootstrap (20,000 resamples) of the score vectors associated with the MLEs of Table2 to tabulate that mixture distribution and estimate the con dence intervals of Table 4.... In PAGE 42: ...stimate the con dence intervals of Table 4. With a few substantial exceptions (e.g., R;88) the con dence intervals do not di er greatly from the intervals obtained by using normal theory with the MLEs and SEs in Table2 (i.... In PAGE 51: ... It is important to keep clear that bHP refers to local variations among equilibria. Numerical computations using the NES data and the parameter MLEs of Table2 show that @ ^ P `|=@| lt; 0 and @ ^ H`|=@` lt; 0 for `; | 2 (0; 1). Moreover, the values ^ P `| = ` are decreasing in |, and the values ^ H`| = | are decreasing in ` for `; | 2 (0; 1) (see Appendix A for the `; | notation).... In PAGE 66: ...6 Note: Entries show the percentage of voters in each year who have the indicated ordering of ideal point and expected party policy positions. Computed using the parameter MLEs in Table2 and... In PAGE 67: ...8 Note: Entries show the percentage of voters in each year for whom the indicated vote choice minimizes xphi ? zphi, ph 2 K, which is the policy-related component of the e ect the voter apos;s choice has on the voter apos;s expected loss. Computed using the parameter MLEs in Table2 and 1976{96 NES data. Each observation is weighted by the sampling weight 1=!i.... ..."

"... In PAGE 3: ..., 1995]. [14] Table1 shows a summary of a priori EC and OC emissions used in the GEOS-CHEM simulation for 1998. The most important global source for both is biomass burning.... In PAGE 6: ... We consider these adjust- ments to be well within the uncertainties on the a priori estimates. The a posteriori values of our adjusted sources are given in Table1 . The increase in the biofuel source is largely determined by the model underestimate of observed OC for the cold season.... In PAGE 11: ... Contribution from different sources types to EC concentrations (mgmC03) in surface air for DJF and JJA. Values are model results for 1998 using a posteriori sources ( Table1 ). See color version of this figure at back of this issue.... ..."