v3.3.0

Extensive work has been put in the automatic model selection when using Taylor polynomials. Instead of generating only the best fitting models per number of terms via leaps, cNORM now generates up to 20 models and screens for those that pass initial consistency checks. This reduces the issue of crossing percentile lines. Additionally, it makes cNORM more robust. If no other criteria like R2 or number of terms are specified, cnorm returns the model with the highest number of terms which meet consistency checks. We ran a huge number of simulations that demonstrate the robustness of this strategy. Thus, while not fully turning the back on parsimony in model selection, this is not our major goal anymore. And hey, we now have a taylorSwift() function!

Changes:

• checkConsistency performance improvement; now runs 100 times faster
• visualization improvement in 'plotDerivative'
• bug in subheadline of plotPercentileSeries fixed
• reduced number of messages
• Starting work on inclusion of regularized Taylor models. Since simulation
  studies with glmnet did not show improvement, we generate much more models
  and preselect those, which pass an initial consistency check.
  Now, the a consistent model with the highest R2 is selected. R^2 and terms
  can of course still be specified as usual.
• plotSubset improved: now indicates, which models did not pass the initial
  consistency check via empty circles
• Plots improved generally, now prints formula and statistical indicators
  in Greek letters and R^2 with the 2 uppercase