  The optimizations of the track fittings require complex simulations of
silicon strip detectors to be compliant with the fundamental properties of the
hit heteroscedasticity. Many different generations of random numbers must be
available with distributions as similar as possible to the test-beam data. A
fast way to solve this problem is an extension of an algorithm of frequent use
for the center of gravity positioning corrections. Such extension gives a
single method to generate the required types of random numbers. Actually, the
starting algorithm is a random number generator, useful in a reverse mode: from
non uniform sets of data to uniform ones. The inversion of this operation
produces random numbers of given distributions. Many methods have been
developed to generate random numbers, but none of those methods is directly
connected with this positioning corrections. Hence, the adaptation of the
correction algorithm to operate in both mode is illustrated. A sample
distribution is generated and its consistency is verified with the
Kolmogorov-Smirnov test. As final step, the elimination of the noise is
explored, in fact, simulations require noiseless distributions to be modified
by given noise models.
