Exposure fitting, curve calibration & reach and frequency allocator #1132
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- in order to use real exposure metrics in modeling, fit_spend_exposure must be inverted into spend ~ exposure - adapted vmax start value to avoid 0 denominator in the inverted equation - adapted spend exposure plots - the impact on saturation curve and budget allocation needs to be reassessed
- now only warns weak relationship when both rsq_nls and rsq_lm are smaller than threshold
- exposure_handling function for better R&F integration and readability - better col readability in dt_plotNLS - simplify dt_transform ETL
This is the proof of concept of a R&F allocator that includes - Simulated R&F data - Implemented multiplicative model - visualisation of surface - R&F allocator with nlopt - constrain validation
- Imp/GRP will be used for parent model fitting. This addition aims to decompose saturated imp into its R&F component with separated saturation - R&F will obtain the same adstock param as imp and be transformed. No separated adstock param estimation - Then adstocked R&F will be fitted with different hill transformations (diff set of alphas /gammas) - The R&F hill params are estimated using a multiplicative equation with Nevergrad - First simulated results shows close to perfect R&F->Imp 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 linear model only: cpm as ratio for spend to exposure translation. - remove minpack.lm / nlsLM dependency - robyn_input() works - to-do: export InputCollect$ExposureCollect$plot_spend_exposure
- update exposure handling, esp. introduce metric "cost per exposure" as linear scaler between expo and spend. - use cpe_window to scale the whole dataset in order to obtain the right spend scale for modeling period. - simplify check_varnames - update check_paidmedia - update check_factorvars
- exposure_handling with scaled spend will now replace respective media exposure vars in dt_transform - adapt model.R, incl. reset run_transformations params to have clearer overview of params needed. - simplify transformation.R by removing unnecessary checks - remove documentation for fit_spend_exposure - include rlang::`:=` operater for easier dynamic variable assignment in the future - check with document update successful. no error /no warning/ no notes
- 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 titles and change y axis.
- use reach Halo cumulative reach and simulated spend - curve fitting with Hill using Nevergrad - early stop convergence with while loop - CI range for alpha & gamma - plotting
- Create robyn_calibrate that consumes curve input and outputs hyperparameter ranges as input. - Rename previous internal robyn_calibrate function as lift_calibration - add support function .dot_product, .qti, .mse_loss, geom_density_ci, check_qti - to-do: Dataframe input df_curve_sot needs to be extended for multiple campaigns. Plot needs to be exported. New checks needed too.
- include inflexion into resultHypParam for better curve calibration handling - fix plot warning
- replace paid_media_spend with paid_media_selected in script - clean up variable retrieval and sorting - deprecate get_hill_params because inflexions are now included in resultHypParam
- fix transformation loop error - add set_default_hyppar for easier testing
…mental/Robyn into reach_and_frequency
- add param force_curve in robyn_calibrate to allow c or s shape control - change inflexion calculation to sum(x) * gamma to increase flexibility of inflexion point
facebook-github-bot
added
the
CLA Signed
simplfy allocator checks
- deprecate robyn_object - simplify usecase - create internal function transform_decomp to standardise adstock -> saturation -> decomp - remove response_wrapper and place with robyn_response - add param calibrate_inflexion in transform_decomp to consume outcome from robyn_calibrate for saturation - update check_metric_type to allow both spend and exposure names
adapt the function to the latest changes of saturation_hill
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Type of change
Unit test (tbc)