dokester/BayesicFitting: First release of BayesicFitting on Zenodo

BayesicFitting is a PYTHON toolbox for (Bayesian) data modelling and evidence calculation. It consists of 3 families of classes. 1. Models that define a parameterised function. Models can be combined in several ways resulting in more complicated models. 2. Fitters that optimise the parameters in the light of the data. All fitters can calculate the evidence as a Gaussian approximation. 3. NestedSampler that performs a fully Bayesian optimisation resulting in the calculation of the evidence and samples from the posterior distribution. It has pluggable priors, error distributions, search engines and hyperparameters BayesicFitting is fully documented, it has test harnesses on most classes, and it has numerous examples in the form of Jupyter notebooks. This is the first release of BayesicFitting on Zenodo. Earlier versions were available on pypi.org and GitHub.com