robyn_mmm | R Documentation |
robyn_mmm()
function activates Nevergrad to generate samples of
hyperparameters, conducts media transformation within each loop, fits the
Ridge regression, calibrates the model optionally, decomposes responses
and collects the result. It's an inner function within robyn_run()
.
robyn_mmm(
InputCollect,
hyper_collect,
iterations,
cores,
nevergrad_algo,
intercept = TRUE,
intercept_sign,
ts_validation = TRUE,
add_penalty_factor = FALSE,
objective_weights = NULL,
dt_hyper_fixed = NULL,
rssd_zero_penalty = TRUE,
refresh = FALSE,
trial = 1L,
seed = 123L,
quiet = FALSE,
...
)
InputCollect |
List. Contains all input parameters for the model.
Required when |
hyper_collect |
List. Containing hyperparameter bounds. Defaults to
|
iterations |
Integer. Number of iterations to run. |
cores |
Integer. Default to |
nevergrad_algo |
Character. Default to "TwoPointsDE". Options are
|
intercept |
Boolean. Should intercept(s) be fitted (default=TRUE) or set to zero (FALSE). |
intercept_sign |
Character. Choose one of "non_negative" (default) or
"unconstrained". By default, if intercept is negative, Robyn will drop intercept
and refit the model. Consider changing intercept_sign to "unconstrained" when
there are |
ts_validation |
Boolean. When set to |
add_penalty_factor |
Boolean. Add penalty factor hyperparameters to glmnet's penalty.factor to be optimized by nevergrad. Use with caution, because this feature might add too much hyperparameter space and probably requires more iterations to converge. |
objective_weights |
Numeric vector. Default to NULL to give equal weights
to all objective functions. Order: NRMSE, DECOMP.RSSD, MAPE (when calibration
data is provided). When you are not calibrating, only the first 2 values for
|
dt_hyper_fixed |
data.frame or named list. Only provide when loading
old model results. It consumes hyperparameters from saved csv
|
rssd_zero_penalty |
Boolean. When TRUE, the objective function DECOMP.RSSD will penalize models with more 0 media effects additionally. In other words, given the same DECOMP.RSSD score, a model with 50% 0-coef variables will get penalized by DECOMP.RSSD * 1.5 (larger error), while another model with no 0-coef variables gets un-penalized with DECOMP.RSSD * 1. |
refresh |
Boolean. Set to |
trial |
Integer. Which trial are we running? Used to ID each model. |
seed |
Integer. For reproducible results when running nevergrad. |
quiet |
Boolean. Keep messages off? |
... |
Additional parameters passed to |
List. MMM results with hyperparameters values.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.