ASKurz/Statistical_Rethinking_with_brms_ggplot2_and_the_tidyverse_2_ed: 99% there

Major improvements include: a corrected workflow for fitting single-level b-spline models (Section 4.5.2), thanks to Stephen Wild; a refined workflow for fitting multilevel b-spline models using the s() function (Section 4.6), thanks to Gavin Simpson; a new bonus section (4.7) on grouping predictors within matrix columns, thanks to insights from Gelman et al (2020) and hints from Paul-Christian Bürkner; a brms solution to the sixth-order polynomial model in Section 7.1.1, thanks again to Stephen Wild; a workflow to reproduce the Metropolis simulation for Figure 9.3, thanks to James Henegan; a corrected workflow for taking fitted()-based random draws for the bonus material in Section 13.5.2.1, thanks to an exchange with Ladislas Nalborczyk; a brms solution to McElreath's bivariate differential equation model in Section 16.4, thanks to Markus Gesmann; better use of geom_area() throughout the book, thanks to insights from Randall Pruim; the adoption of a CONTRIBUTING section on GitHub, thanks to Brenton M. Wiernik; improved table workflow with the flextable package; and all models have been refit using brms version 2.15.0