# stochprofML 2.0.3

- 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.
- Created a github repository: https://github.com/fuchslab/stochprofML
- Extended n the number of cells that was constant over all samples to be flexible to be different for each sample.
- Added possibility to put in the predefined number of cells when using the random number generators r.sum.of.mixtures by specifying N.matrix
- Add the mixed density calculator when calculating the density of a distribution with a specific n.vector as input.
- Changed all functions that use the fixed n to be able to use a vector n
- Added doi of Tirier et al. (2019) paper where this was first implemented and used
- Minor fixes of textings