### Table 8.1 summarizes the asymptotic criteria for D-optimality derived in

1999

### Table 2.1: Comparison of worths for three di erent approaches. In the table, n is optimal sample size, and ^ n is asymptotically optimal sample size. W is optimal worth, and ^ W is worth calculated at ^ n. The worth ~ W is calculated according to (2.25).

### Table 1: Asymptotic optimal bandwidth (3.4) for Poisson models with uniform weight function again the uniform distribution on [?2; 2] and the function (x) = logf (x)g is given by Example 4. (x) = 1:5 sin(2x) + 1:25

1999

"... In PAGE 13: ... (x) = 7[expf?(x + 1)2g + expf?(x ? 1)2g] ? 5:5 Example 3. (x) = 2 ? x2: These curves appear as the solid line in part (c) of Figures 1-3 and the asymptotic optimal band- widths hopt for n = 250; 500; 1000 were given in Table1 of Fan, Farmen and Gijbels (1997). For each of the above examples, we conducted 400 simulations with sample size n = 250; 500; 1000.... In PAGE 16: ...5 under the Poisson distributions. For these Poisson models, the asymptotic optimal bandwidths hopt with the uniform weight function on [?2; 2] are summarized in Table1 for n = 250; 500 and 1; 000. Figures 4(a){(c) compare the performance of the least-squares, the one-step, and the local likelihood estimator using bandwidths h = hopt=2; hopt and 2hopt under the Poisson models.... ..."

Cited by 9

### Table 2: Types of functions, their optimization algorithms, asymptotic time and space re- quirements for these algorithms, and examples of functions in these categories. Type Algorithm Time Space Functions

"... In PAGE 16: ... In binary induction TSE is more useful. Table2 summarizes the current knowledge of optimization... ..."

### Table 4. Optimization of a heat exchanger network { Note that Run 1 converges asymptotically.

"... In PAGE 21: ... In Run 6, the e ect of updating the bounds on only a fraction of the continuous variables was studied.The results are shown in Figure 6 and Table4 . Branching on the continuous variables only results in slow asymptotic convergence of algorithm to the global optimum solution (Run 1).... ..."

### Table 1 - Optimization of a heat exchanger network Note that Run 1 converges asymptotically

1997

Cited by 11

### Table 2: Running the algorithm with 3 processors: t0 = 3, t1 = 5, and t2 = 8. Finally, we point out that our modi ed heuristic \converges quot; to the original asymptotically optimal heuristic. For a chunk of size C = L PP?1 i=0 1 ti , where L = lcm(t0; t1; : : : ; tP?1) columns, we obtain the optimal cost

"... In PAGE 13: ...To understand how the algorithm works, we present a small example with P = 3, t0 = 3, t1 = 5, and t2 = 8. In Table2 , we report the best allocations found by the algorithm up to s = 7. The entry \Selected j quot; denotes the value of j that is chosen to build the next allocation.... ..."