itial number of observations per algorithm
(<code>nstart</code>) should be relatively high. For the parametric case
we recommend between 10 and 20 if outliers are not expected, or between 30
and 50 if that assumption cannot be made. For the bootstrap approach we
recommend using at least 20. However, if some distributional assumptions can
be made - particularly low skewness of the population of algorithm results on
the test instances), then <code>nstart</code> can in principle be as small as 5 (if the
output