now construct a sequence (not necessarily a Markov sequence yet) with any state x EG as
the first element. We then change x a little bit: x' = x + Ax, and automatically accept x'
as the next element in the sequence if 7(x') > 7(x). If however 7(x') < 7(x) we accept it
with probability p = 7(x')/w(x). In practice this is done by having the computer generate
a (pseudo-)random number r uniformly distributed between 0 and 1 and accepting the
change if r < p. If the change is rejected then by default the next element is x, the same
as the current one. This way new elements are generated, or rather selected, one by one
from state-space. Notice that Ax is in general different for each time the state is changed
and in some sophisticated models it is generated stochastically using information about
7 to maximize acceptance rates. The procedure generates a sequence (xk)O