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Clarke (1983) justifies (8.2) in a general framework by proving the F'rkchet differentiability of M-estimators even when $ is not smooth. Writing (8.2) we see that the influence curve of an M-estimator is proporIC = tional to $ and moreover that the dependence on the distribution is subsumed into the proportionality constant (Goodall, 1983).

a b g b bs 2 2 2-48

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The integral in Eq. 2-46 yields simple integrals for s values of 0, 1, and 1. The dependencies of a, b, and g on t in these instances are 1. For s 1, that is, k2 k1 ,

b 1 g a 1 2t 2-49

The IC is defined similarly for the multivariate case. In the case of M-estimators, we get IC(zIT, = F)rl where

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2. For s 0, that is, k1 ) k2 , where k1 has some value and k2 ! 0: B0 groups do not react (g 1) and

3. For s 1, that is, k2 ) k1 , where k2 has some value and k1 ! 0: B groups do not react b 1 and

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For almost all other values of s the integral in Eq. 2-46 must be numerically evaluated. The results of such calculations are presented in graphical form in Figs. 2-3 and 2-4 as plots of a, b, and g versus log t for s values of 1 and larger [Ozizmir and Odian, 1980]. There is no need for plots for s < 1, since the B and B0 groups have interchangeable roles due to the symmetry of the reaction system. a at any time is exactly the same for s z or s 1=z, where z is any number. The only difference for an s value of z or 1=z is whether it is the B or B0 type of group, which reacts rapidly while the other reacts slowly. Figure 2-3 gives b and g as a function of t. When s 1 both b and g decay at the same rate according to Eq. 2-49. As s increases the b plots move sharply above the plot for s 1 since B groups react more slowly with A. Although k2 is xed, increasing values of s help move the g plots gradually below the plot for s 1, since B groups reacting more slowly with A leaves comparably more [A] for

an R x matrix, where R is the total number of weights in the MLP model. Hence we can see that the R-dimensional IC (where all R parameters may vary at once) is given by linear combinations of the onedimensional ICs (where only one parameter is allowed to vary and the others are held constant).

Fig. 2-3 Decay in b and g with time in the polymerization of A A with B B0 . b plots are indicated by 4; g plots, by *. Values of s are noted for each curve. After Ozizmir and Odian [1980] (by permission of Wiley-Interscience, New York).

B0 groups to react with. As s ! 1 the condition is reached in which [B] remains constant at B 0 during the complete decay of B0 according to Eq. 2-51b. Figure 2-4 shows the decay in a and the corresponding increase in X n with t (since X n 1=a). It becomes progressively more dif cult to achieve high degrees of polymerization in reasonable times for reaction systems of s > 1. At suf ciently large s (small k1 ) the

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