v3.8.0 - Bootstrapped CI, Immediate vs Carryover, Multi-channel calibration

• Feat: Added in-cluster bootstrapped confidence intervals (CI) for ROAS and CPA. We treat each cluster of Pareto-optimal model candidates as a sample from a local optimum of the entire population. Default parameters can be customized manually with boot_n and sim_n arguments.
• Feat: New robyn_calibrate() function that replaces previous un-exported function calibrate_mmm(). The new calibration method is able to separate immediate & carryover effects. When calibrating using experimental results, only the immediate response and its future carryover serve as a calibration target, as opposed to previously the total response. The historical response is excluded from calibration.
• Feat: Enabled multi-channel calibration so we can use experiments that measured more than one channel with a single experiment to be used for calibration (i.e. incrementality experiment measured all fb but you had fb_brand and fb_perf as two separate media channels/variables).
• Feat: Added 2 new plots into model one-pager: bootstrapped CI plot and immediate vs carryover response plot.
• Feat: Changed default Pareto-fronts from 3 to ”auto" to pick the N that contains at least 100 models (threshold can be changed manually with min_candidates parameter).
• Recode: improved CodeFactor's code quality score from C- to A
• Feat: Additional CI outputs containing revamped plot and CSV file.
• Feat: Enabled turning off parallel calculations when cores = 1.
• Fix: Fixed few minor bugs and doumentations (#496, #506, #507, #515)

Full Changelog: v3.7.2...v3.8.0