dmphillippo/multinma: v0.3.0

This release adds new features for specifying baseline distributions when producing absolute predictions, and fixes errors that occurred when specifying certain types of models with contrast-based data, along with other improvements and fixes. Feature: Added baseline_type and baseline_level arguments to predict.stan_nma(), which allow baseline distributions to be specified on the response or linear predictor scale, and at the individual or aggregate level. Feature: The baseline argument to predict.stan_nma() can now accept a (named) list of baseline distributions if newdata contains multiple studies. Improvement: Misspecified newdata arguments to functions like relative_effects() and predict.stan_nma() now give more informative error messages. Fix: Constructing models with contrast-based data previously gave errors in some scenarios (ML-NMR models, UME models, and in some cases AgD meta-regression models). Fix: Ensure CRAN additional checks with --run-donttest run correctly