If
is chosen to be too low then a significant amount of
energy minimisation is included and the numerical stability
deteriorates. Using a value of
slightly below
appears to offer no significant advantages.
A direct comparison of the different variance-like objective
functions is made in figure 5.7. The behaviour of the following
objective functions are displayed: (i)
, (ii)
with
a.u., (iii)
, and (iv) a variant of
with the
maximum value of the weights limited to 10 times the mean weight.
Limiting outlying values of the local energy improves the behaviour of
all the objective functions, so in each case we have limited them
according to equation 5.15 with
=8. The mean values of the
objective functions are plotted in figure 5.7a, which shows them
to behave similarly, with the positions of the minima being almost
indistinguishable. However, the curve for the variant of
with
limited weights is somewhat flatter, which is an undesirable feature.
The standard deviations of the objective functions are plotted in
figure 5.7b, and here the differences are more pronounced. The
unweighted variance,
, has the smallest variance, which is slightly
smaller than that of the variant of
with strongly limited weights.
The variances of the objective functions which include the full
weights increase rapidly away from
=0. This rapid increase is
highly undesirable and could lead to numerical instabilities.