robyn_calibrate: Robyn Calibration Function - BETA

In Robyn: Semi-Automated Marketing Mix Modeling (MMM) from Meta Marketing Science

Robyn Calibration Function - BETA

Description

robyn_calibrate() consumes source of truth or proxy data for saturation or adstock curve estimation. This is an experimental feature and can be used independently from Robyn's main model.

Usage

robyn_calibrate(
  df_curve = NULL,
  curve_type = NULL,
  force_shape = NULL,
  hp_bounds = NULL,
  max_trials = 10,
  max_iters = 2500,
  loss_min_step_rel = 1e-04,
  loss_stop_rel = 0.05,
  burn_in_rel = 0.1,
  sim_n = 30,
  hp_interval = 0.5,
  quiet = FALSE,
  ...
)

Arguments

df_curve	data.frame. Requires two columns named spend and response. Recommended sources of truth are Halo R&F or Meta conversion lift.
curve_type	Character. Currently only allows "saturation_reach_hill" and only supports Hill function.
force_shape	Character. Allows c("c", "s") with default NULL that's no shape forcing. It's recommended for offline media to have "c" shape, while for online can be "s" or NULL. Shape forcing only works if hp_bounds is null.
hp_bounds	list. Currently only allows Hill for saturation. Ranges for alpha and gamma are provided as Hill parameters. If NULL, hp_bounds takes on default ranges.
max_trials	integer. Different trials have different starting point and provide diversified sampling paths. Default to 10.
max_iters	integer. Loss is minimized while iteration increases. Default to 2500.
loss_min_step_rel	numeric. Default to 0.01 and value is between 0-0.1. 0.01 means the optimisation is considered converged if error minimization is <1 percent of maximal error.
loss_stop_rel	numeric. Default is 0.05 and value is between 0-0.5. 0.05 means 5 percent of the max_iters is used as the length of iterations to calculate the mean error for convergence.
burn_in_rel	numeric. Default to 0.1 and value is between 0.0.5. 0.1 means 10 percent of iterations is used as burn-in period.
sim_n	integer. Number of simulation for plotting fitted curve.
hp_interval	numeric. Default to 0.95 and is between 0.8-1. 0.95 means 2.5 - 97.5 percent percentile are used as parameter range for output.
quiet	Boolean. Keep messages off?
...	Additional parameters passed to robyn_outputs().

Value

List. Class: curve_out. Contains the results of all trials and iterations modeled.

Examples

## Not run: 
# Dummy input data for Meta spend. This is derived from Halo's reach & frequency data.
# Note that spend and response need to be cumulative metrics.
data("df_curve_reach_freq")

# Using reach saturation from Halo as proxy
curve_out <- robyn_calibrate(
  df_curve = df_curve_reach_freq,
  curve_type = "saturation_reach_hill"
)
# For the simulated reach and frequency dataset, it's recommended to use
# "reach 1+" for gamma lower bound and "reach 10+" for gamma upper bound
facebook_I_gammas <- c(
  curve_out[["curve_collect"]][["reach 1+"]][["hill"]][["gamma_best"]],
  curve_out[["curve_collect"]][["reach 10+"]][["hill"]][["gamma_best"]])
print(facebook_I_gammas)

## End(Not run)

Robyn documentation built on July 3, 2025, 1:09 a.m.