export function set.model.function() as it is needed when using for example d.sum.of.mixtures.
in stochprof.results generate a duplicate of all previous results perform rounding of parameters and target and remove duplicates in the original result table, like this all results in the final output and used inside optimization are not rounded and belong 100% to the target negative loglikelihodd and BIC.
stochprofML 2.0.2
d.sum.of.lognormals: If it is not a real sum but only one summand use dlnorm directly
in d.sum.of.types (all models) and correspondingly d.sum.of.lognormal.types: bug fix, as mu.vector and sigma.vector were wrongly filled for TY > 2.
small foramting changes on Help pages
stochprofML 2.0.1
Deleted the argument "logdens" in mix.d.sum.of.mixtures because of a bug if set to TRUE.
stochprofML 2.0.0
Added a NEWS.md file to track changes to the package.