### Table 3: Two-Stage Least-Squares Estimates

"... In PAGE 9: ... We next conduct a 2SLS analysis in which LNDIST, INITIAL, EDU, REF, LPRIV and SPRIV are used as instruments for NEWENT in a first-stage regression, and the fitted value of NEWENT is combined with the remaining variables (IO, DEFENSE and PRICE) in a second- stage growth regression. The estimates we obtain are reported in Table3 . Consider first the NEWENT regression.... In PAGE 9: ... The coefficients on LNDIST and SPRIV are statistically insignificant, but the remaining variables each appear to have a significant relationship with NEWENT, both statistically (at the 5% level) and quantitatively. To characterize quantitative significance, we report the impact on NEWENT of a one-standard-deviation increase in each variable in the last column of Table3 . For example, a one-standard-deviation increase in initial income (representing an 79% increase in the purchasing power of money income per capita in 1993:IV, as reported in the sixth column of Table 3) corresponds with an additional 0.... In PAGE 9: ... To characterize quantitative significance, we report the impact on NEWENT of a one-standard-deviation increase in each variable in the last column of Table 3. For example, a one-standard-deviation increase in initial income (representing an 79% increase in the purchasing power of money income per capita in 1993:IV, as reported in the sixth column of Table3 ) corresponds with an additional 0.549 additional new enterprises per 1000 inhabitants on average across regions.... In PAGE 10: ... A similar observation holds for the reformist voting proxy. The 2SLS estimates reported in Table3 are of course based on identifying restrictions used to select instruments for NEWENT in the first-stage regression. The restrictions involve the exclusion of the variables used as instruments from the second-stage growth regression.... In PAGE 10: ...586), while the quantitative significance of the remaining variables is negligible by comparison. Thus there is reasonable empirical support for the identifying assumptions upon which the results of Table3 are based. We conclude our analysis with an assessment of the influence of the outlier regions.... ..."

### Table 4: Comparison of Two-stage Methods for LDA

"... In PAGE 10: ...5% 1% 8 Conclusion To address the problem of dimension reduction of very high- dimensional or undersampled data, we have compared four seemingly different methods. Our results are summarized in Table4 , where q = rank(A), p = rank(Hm), and the complete orthogonal decomposition is referred to as URV. After showing that both LSI and PCA maximize J2(G) = trace(GT SmG) over all G with GT G = I, we confirmed the preservation of trace(Sw) and trace(Sb) with either method or the computationally simpler QRD.... ..."

### Table 4: Comparison of Two-stage Methods for LDA

"... In PAGE 8: ... 8 Conclusion To address the problem of dimension reduction of very high- dimensional or undersampled data, we have compared four seemingly different methods. Our results are summarized in Table4 , where q = rank(A), p = rank(Hm), and the complete orthogonal decomposition is referred to as URV. After showing that both LSI and PCA maximize J2(G) = trace(GT SmG) over all G with GT G = I, we confirmed the preservation of trace(Sw) and trace(Sb) with either method or the computationally simpler QRD.... ..."

### Table 4: Comparison of Two-stage Methods for LDA

2003

"... In PAGE 11: ...5% 1% 8 Conclusion To address the problem of dimension reduction of very high- dimensional or undersampled data, we have compared four seemingly different methods. Our results are summarized in Table4 , where q = rank(A), p = rank(Hm), and the complete orthogonal decomposition is referred to as URV. After showing that both LSI and PCA maximize J2(G) = trace(GT SmG) over all G with GT G = I, we confirmed the preservation of trace(Sw) and trace(Sb) with either method or the computationally simpler QRD.... ..."

### Table 1: Two-Stage LCGs Statistics

"... In PAGE 6: ... Here after a detailed example of a PRNG in the TSRG family whose randomizer is LCG with modulus 5 and multiplier 3 with initial condition 1 denoted as C4B4BHBN BFBN BDB5 and adapted Lehmer generator C4B4BJBN BHB5. Table1 summarizes the results, which imply that 3 is the total average and 2 is the bad initial condition and TSRG period D4 BP B4BI A2 BGB5BPBE BP BDBE.... ..."

### Table 1: Two-Stage LCGs Statistics

"... In PAGE 6: ... Here after a detailed example of a PRNG in the TSRG family whose randomizer is LCG with modulus 5 and multiplier 3 with initial condition 1 denoted as a164 a11a87a101a18a14a61a165a18a14a22a33a35a24 and adapted Lehmer generator a164 a11a149a166a57a14a100a101a4a24 . Table1 summarizes the results, which imply that 3 is the total average and 2 is the bad initial condition and TSRG period a130 a7a167a11a87a168 a111 a113a54a24a36a108a95a60a49a7a104a33a38a60 .... ..."

### Table. 3 Optimization Results of the Two-Stage Method

Cited by 3

### Table 3: Summary of results from using the two-stage approach and the

"... In PAGE 11: ...he cost for grade C is 0). Thus the total quality cost F = Q + C = 19:35. Unless otherwise stated, the unit for Q is million yen /year for the rest of the paper. The results of the initial design are summarized in Table3 . The same table also contains results given by Taguchi apos;s two-stage approach as performed by Mori (4).... ..."

### Table 1: Design specifications for two-stage op-amp.

1998

"... In PAGE 5: ... The load capacitance is 5pF and the supply voltages are Vdd = 5V and Vss = 0V. A simple design example Table1 describes the sample design problem, and shows the perfor- mance of the design obtained by GPCAD using GP1 models, and the simulated performance with BSIM1 models (HSPICE level 13). The objective was to maximize the unity gain bandwidth subject to the other given constraints.... ..."

Cited by 19

### Table 1. Outcomes of the two-stage process for site i

2005

"... In PAGE 3: ... The corresponding second-stage data are the number, ril greaterorequalslant 0, of units that were resampled from each initial negative pool, indexed by l, and the number, sil, that are actually D. Table1 illustrates the situation. While Johnson and Gastwirth (2000) assumed that data would be collected from multiple sites, they treated the data as a random sample from a single population.... ..."