  A novel method is presented to compute the exit time for the stochastic
simulation algorithm. The method is based on the addition of a series of random
variables and is derived using the convolution theorem. The final distribution
is derived and approximated in the frequency domain. The distribution for the
final time is transformed back to the real domain and can be sampled from in a
simulation. The result is an approximation of the classical stochastic
simulation algorithm that requires fewer random variates. An analysis of the
error and speedup compared to the stochastic simulation algorithm is presented.
