v3.12.0 [GitHub R]

What's Changed

Exposure fitting, curve calibration & reach and frequency allocator (#1132)

• feat: enable exposure fitting

• Exposures (Imp/GRP etc) will be prioritised over spend for parent model fitting
• Deprecate function fit_spend_exposure, incl. Michaelis Menten. Nonlinear fitting between spend and exposure wasn't improving fitting significantly. Instead, future curve calibration feature will aim to improve curve identification.
• Use cpe (cost per exposure) as ratio for spend to exposure translation. use cpe_window to scale the whole dataset in order to obtain the right spend scale for modeling period.
• remove minpack.lm / nlsLM dependency
• update exposure plot

• feat: The curve calibrator - robyn_calibrate

• Simulate cumulative R&F dataset with frequency bucket
• add beta coef besides alpha and gamma to nevergrad hyperparameter to improve curve fit
• plot with freq_bucket as well as onepager per trial
• add df_curve_reach_freq as dummy dataset
• create robyn_calibrate that consumes curve input and outputs hyperparameter ranges as input.
• Rename previous internal robyn_calibrate function as lift_calibration
• early stop convergence with while loop
• update documentation

• prototype: reach and frequency allocator
  This is the proof of concept of a R&F allocator that includes

• Simulated R&F data
• The R&F hill params are estimated using a multiplicative equation with Nevergrad
• visualisation of surface
• R&F allocator with nlopt
• constrain validation

• update: checks, input, transformation & website

• simplify various check functions
• adapt model.R, incl. reset run_transformations params to have clearer overview of params needed. simplify transformation.R by removing unnecessary checks
• In model.R & pareto.R: remove decompSpendDist from both scripts to reduce memory leak. Use xDecompAgg subsets instead
• In transformation.R & response.R: unify transformation namings in run_transformation and robyn_response
• In response.R: remove exposure extrapolation because it's already done in robyn_input. Also add inflexion point to output.
• In plots.R: fix onepager saturation plot issues
• In pareto.R: rewrite run_dt_resp() as response_wrapper and align transformation logic & naming.
• In pareto: Replace foreach response loop with lapply for simplicity.
• In pareto.R: Simplify plot data generation process, esp for saturation curve plot, actual vs predicted plot & immediate vs carryover plot.
• In pareto.R: Remove redundancy in xDecompVecCollect -> remove type rawMedia, rawSpend, predictedExposure, saturatedMedia & saturatedSpendReversed. Only keep adstockedMedia & decompMedia for response curve plotting.
• add set_default_hyppar for easier testing
• website update for all above changes

Contributors

@gufengzhou, @laresbernardo

Full Changelog: v3.11.0...v3.12.0

v3.11.1 [CRAN]

What's Changed

• fix: one-pager decomp labels and warning by @laresbernardo in #1011

v3.11.0 [CRAN]

What's Changed

• Add objective weights by @gufengzhou in #826
• build(deps): bump @babel/traverse from 7.21.5 to 7.23.2 in /website by @dependabot in #842
• feat: check and fix all_sol_json & new pareto_df parameters inputs by @laresbernardo in #843
• feat + fix: bundle fixes and improvements on json files by @laresbernardo in #852
• fix: compatibility with legacy files on robyn_recreate() by @laresbernardo in #865
• Fix #850 & #838 by @michellegrushkometa in #864
• Robyn api by @yu-ya-tanaka in #863
• fix: crashed cut() when monthly data by @laresbernardo in #868
• fix: when all values on a column are negative crash by @laresbernardo in #871
• fix: winsorize errors with na.rm = TRUE #872 + InputCollect print when no prophet by @laresbernardo in #875
• Bundle of small fixes and feats by @laresbernardo in #882
• fix: foreach seed for reproducibility + dt_simulated_weekly dataset by @laresbernardo in #907
• Robyn api update notebook and endpoint by @yu-ya-tanaka in #912
• fix: avoid overwriting csv when scenario changes by @laresbernardo in #913
• fix: intercept param in outputs + ts_validation plot for convergence by @laresbernardo in #917
• build(deps): bump follow-redirects from 1.15.3 to 1.15.4 in /website by @dependabot in #899
• feat: enable baseline_level param for decomp_plot() + let NULL solID when single model available +docs: update robyn_response() examples by @laresbernardo in #923
• docs: clarify objective_weights order by @laresbernardo in #929
• feat: add clusters information to one-pagers, fix metric notes, reduce texts sizes, no ng check to recreate + fix: RNG warning by @laresbernardo in #928
• feat: keep custom exported data from JSON when recreating model & use raw_data if available + update docs by @laresbernardo in #930
• fix: mediaVecCollect's organic vars weren't being multiplied by coef values + InputCollect print when no prophet country set by @laresbernardo in #936
• fix: One or both dimensions exceed the maximum (50000px) error #874 by @laresbernardo in #939
• build(deps): bump follow-redirects from 1.15.4 to 1.15.6 in /website by @dependabot in #941
• build(deps): bump webpack-dev-middleware from 5.3.3 to 5.3.4 in /website by @dependabot in #943
• build(deps): bump express from 4.18.2 to 4.19.2 in /website by @dependabot in #947
• fix: target = 1 error and better constraints check by @laresbernardo in #942
• Fixed error when ts_validation is false. by @yu-ya-tanaka in #965
• bl01: refresh fixes and improvements + others by @laresbernardo in #969
• build(deps): bump braces from 3.0.2 to 3.0.3 in /website by @dependabot in #997
• fix: refresh hyps check + use data available in json + refresh hyps + upper constraints fix when higher than mean by @laresbernardo in #974
• build(deps): bump ws from 7.5.9 to 7.5.10 in /website by @dependabot in #999
• docs: CRAN 3.11.0 by @laresbernardo in #1001

New Contributors

• @yu-ya-tanaka made their first contribution in #863

Full Changelog: v3.10.5...v3.11.0

v3.10.5: Objective function weight, Meta MMM API beta, website tab "Features" revamp, bug fixes

• Feat: New arg objective_weights in robyn_run() to allow manual tuning of weights for objective functions (NRMSE, DECOMP.RSSD, MAPE.LIFT). Default weight is even weights c(1,1,1). Note: This is experimental and there's no guidance on how weights biases modelling. Commit here
• Feat: Meta MMM API connector demo, a beta script. Commit here
• Doc: Updated and revamped the website "features" tab, also reorganised the navigation. see here

Full Changelog: v3.10.3...v3.10.5

v3.10.3: Objects size reduction, RSSD penalty for 0 effect media [CRAN]

More details on Facebook's Robyn Community post

• Feat: Reduced object sizes up to 88% #687
• Feat: RSSD penalty for 0 media effects media (parameter) #680
• Feat: Always constraint prophet coefficients to 0-1 #686
• Feat: Windsorized NRMSE on multi-objective optimization plots [1/500 default threshold] to avoid extreme skewness #693
• Feat: New intercept parameter passed to glmnet() #722
• Fix: Return meaningful error when, after filtering by modeling window, a variable has no variance #619
• Fix: Removed negative carryover outputs for Weibull PDF adstock #706
• Fix: Correctly pass plot_folder input on robyn_refresh() #708

Full Changelog: v3.10.2...v3.10.3

v3.10.2: Refresh model selection and small bugs

• Fix: when running robyn_refresh(), select the refresh model by error_score value correctly #674
• Fix: pass penalty.factor when dropping intercept too
• Fix: when importing holidays data, force date values as dates #663 by @richin13
• Docs: update several documentations across functions and site

New Contributors

• @richin13 made their first contribution in #663

Full Changelog: v3.10.1...v3.10.2

v3.10.1 - New “Target Efficiency” scenario for budget allocator

More details in post: Hitting ROAS target using Robyn’s budget allocator

• Feat: allocator's new scenario "target_efficiency" for ROAS/CPA target #648
• Fix: inverted CPA in allocator viz table #640
• Fix: re-enable experimental add_penalty_factor feature
• Fix: re-include spend from skipped channels #645

Full Changelog: v3.10.0...v3.10.1

v3.10.0: Allocator upgrade

More details in post: The convergence of marginal ROAS in the budget allocation in Robyn

• Feat: all new one-pager for robyn_allocator() showing initial, bounded and less-bounded scenarios, using last month's worth of data by default. Relevant changes from previous versions: initial spend is now mean of date range selected, not non-zero mean anymore + deprecated "max_response_expected_spend" scenario + carryover information is now provided in the curves + inform user when budget is topped and can't be fully allocated + added mROAS / mCPA for better understanding of allocation. And one step closer to the forecast functionality. #600
• Feat: robyn_response() now requires date or date range for adstocking (last period by default) and accepts single or multiple values to return different use cases and scenarios.
• Feat: new transform_adstock() exported wrapper function.
• Feat: added NRMSE validation on test set.
• Feat: added prophet monthly component.
• Fix: issue with differences on OutputCollect$OutputModels and OutputModels to produce ts_validation plot. #596
• Fix: added correct solID for fixed hyperparameters (not 1_1_1).
• Recode: reduced the size of xDecompVec on OutputCollect to only pareto-front models.
• Recode: got rid of "ggcorrplot" and "rPref" package dependencies.
• Docs: added blueprint link to demo.R.

Full Changelog: v3.9.0...v3.10.0

v3.9.0: Time-series validation feature [CRAN]

• Feat: new time series validation via time-series train/val/test dynamic splits and Adjusted R2 and NRMSE metrics reported for each group feature #545. We are adding an additional train_size hyperparameter to pick the size of the training size, which by default will iterate in the range of 0.5-0.8. Given it's a hyperparameter, you can change the range or fix the value manually. Turn on/off this feature using the ts_validation new parameter on robyn_run(); default is set to FALSE for now. This is an important step for the forecasting coming function.
• Feat: new ts_validation() function to plot time-series validation and convergence results. Generated and exported by default when ts_validation = TRUE, and when export = TRUE, creating ts_validation_plot.png file.
• Fix: updated Adjusted R2 calculation (get_rsq()) for time-series validation using same denominator.
• Fix: results are not sorted by lowest errors now to keep iteration results actual order.
• Feat: added prophet monthly component to enrich decomposition results #525
• Fix: correct solID (not "1_1_1") for fixed hyperparameters recreated models.
• Recode: reduced the size of xDecompVec on OutputCollect by keeping pareto-front models only.
• Docs: changed standard inputs on demo.R file for modeling window to include more data (3 years by default).

New Contributors

• @michellegrushkometa made their first contribution in #559

Full Changelog: v3.8.2...v3.9.0

v3.8.2: Memory friendly outputs, progress bars for Pareto-front models, bugs and docs

• Feat: new status bars for Pareto-Front models per trial to provide information on calculation status
• Feat: included carryover results into pareto_aggregated.csv output and OutputCollect$xDecompAgg$carryover_pct
• Feat: new error message shows which hyperparameters inputs are missing #543
• Fix: substantially reduced the size of robyn_run() and robyn_outputs() results (around -80% compared with 3.8.1 version's size) by removing redundant and unused data from outputs #534
• Fix: invalid argument type in check_factorvars() and issue recreating calibrated models #520
• Fix: add_penalty_factor parameter now works correctly with JSON files and robyn_refresh() #543
• Fix: correct hyper-parameters length for custom data #533
• Fix: bug in RobynLearn when checking numerical data #532
• Fix: removed .iData format for legacy demo .RData files
• Fix: passing custom pareto_fronts input instead of "auto" now works as expected
• Docs: updated released version on website, meta.com emails, update CRAN link on robyn_update()

Full Changelog: v3.8.0...v3.8.2