lightweight_mmm
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LightweightMMM 🦇 is a lightweight Bayesian Marketing Mix Modeling (MMM) library that allows users to easily train MMMs and obtain channel attribution information.
Maybe I am missing something but why you have a method for calculating carryover effects and adstock effects? [](https://lightweight-mmm.readthedocs.io/en/latest/api.html#lightweight_mmm.media_transforms.carryover) [](https://lightweight-mmm.readthedocs.io/en/latest/api.html#lightweight_mmm.media_transforms.adstock) Looking at the documentation the adstock method refer to the...
how different it is from Robyn https://github.com/facebookexperimental/Robyn
Hi, Everything seems to be running smoothly - getting good results and am able to run plot_media_channel_posteriors(), plot_model_fit(), plot_out_of_sample_model_fit(), plot_media_baseline_contribution_area_plot() and plot_bars_media_metrics(). However, when I try to chart the plot_response_cruves:...
Hi there, I was trying to run LMMM package on my new M2 laptop, but on the very beginning code where it tried to import jax.numpy, it returned an error...
Reading the documentation on [Media Optimization](https://lightweight-mmm.readthedocs.io/en/latest/api.html#lightweight_mmm.optimize_media.find_optimal_budgets), I have one doubt. When we are trying to optimize the media spend what is the argument "prices". _"prices – An array with shape...
Hello, I'm trying to plot the prior and posterior distributions of my model's parameters. When do mmm.fit(..., weekday_seasonality = False), the function mmm.plot_prior_and_posterior(...) plots are returned. When do mmm.fit(..., weekday_seasonality...
I have seen many notebook codes where the "costs" variable isnt splited between train and test ser before model fitting. Is it correct ? All the other variables are splited,...
Running into an error where I am following the tutorial at the example at https://github.com/google/lightweight_mmm/blob/main/examples/simple_end_to_end_demo.ipynb but when I use ``` plot.plot_out_of_sample_model_fit(out_of_sample_predictions=new_predictions, out_of_sample_target=target_scaler.transform(target[split_point:])) ``` I am getting an error `ValueError: Length...
Hello, I'm pleased to inform bebefical information. Yesterday (Feb 17th) jax have been upgaraded to version 0.4.4. So jax.vmap function does'nt work well on google colobo. Therfore I offer resolution...
