Implement a CovariatePopulationModel

[DavAug]

A CovariatePopulationModel extends PopulationModel and

• is instantiated with an instance of a PopulationModel and an instance of a CovariateModel.
• extends all data related methods by an additional argument covariates which accepts the an array-like object of shape (n, c), where n is the number of individuals and c the number of covariates.

Extending the PopulationModel will lead to problems with the ReducedPopulationModel and the HierarchicalLogLikelihood, where we have to distinguish the covariate model from the simple model.
Make ReducedModel compatible with the covariate model by optionally allowing to pass covariates and introduce internal bookleeping variable. In the hierarchical model we first check for popmodels and next for covariate dependence.

Make sure that the CovariatePopulationModel works with

• HierarchicalLogLikelihood
• PopulationPredictiveModel
• PosteriorPredictiveModel
• ProblemModellingController
  • set_data
  • set_covariate_model (Will not be implemented. Is unnecessary because CovariatePopulationModels can just be constructed manually and set with set_population_model).
  • get_predictive_model
  • get_log_posterior