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v3.6.0 - Add new hyperparameter, new convergence metric, improved response function, prints and better allocation stability
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@gufengzhou gufengzhou released this 22 Feb 11:42
· 886 commits to main since this release
v3.6.0
95091c9

What's New in v3.6.0

  • New hyperparameter "lambda" finds MOO-optimal lambda and thus removes the need of manual lambda selection.
  • New optional hyperparameter penalty.factor that further extends hyperparameter spaces and thus potentially better fit.
  • New optimisation convergence rules & plots for each objective function showing if set iterations have converged or not (NRMSE, DECOMP.RSSD, and MAPE if calibrated)
  • Improved response function now also returns the response for exposure metrics (response on imps, GRP, newsletter sendings, etc) and plots. Note that argument names and output class has changed. See updated demo.R for more details.
  • More budget allocation stability by defaulting fitting media variables from paid_media_vars to paid_media_spends. Spend exposure fitting with Michaelis Menten function will only serve robyn_response() function output and plotting. robyn_allocator() now only relies on direct spend - response transformation.
  • Default beta coefficient signs: positive for paid & organic media and unconstrained for the rest. Users can still set signs manually.
  • New print methods for robyn_inputs(), robyn_run(), robyn_outputs(), and robyn_allocator() outputs to enable visibility on each step's results and objects content.

Full Changelog: v3.5.1...v3.6.0

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