| \n", + " | date_week | \n", + "y | \n", + "x1 | \n", + "x2 | \n", + "event_1 | \n", + "event_2 | \n", + "dayofyear | \n", + "
|---|---|---|---|---|---|---|---|
| 0 | \n", + "2018-04-02 | \n", + "3.984662 | \n", + "0.318580 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "92 | \n", + "
| 1 | \n", + "2018-04-09 | \n", + "3.762872 | \n", + "0.112388 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "99 | \n", + "
| 2 | \n", + "2018-04-16 | \n", + "4.466967 | \n", + "0.292400 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "106 | \n", + "
| 3 | \n", + "2018-04-23 | \n", + "3.864219 | \n", + "0.071399 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "113 | \n", + "
| 4 | \n", + "2018-04-30 | \n", + "4.441625 | \n", + "0.386745 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "120 | \n", + "
| \n", + " | date_week | \n", + "y | \n", + "x1 | \n", + "x2 | \n", + "event_1 | \n", + "event_2 | \n", + "dayofyear | \n", + "t | \n", + "
|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "2018-04-02 | \n", + "3.984662 | \n", + "0.318580 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "92 | \n", + "0 | \n", + "
| 1 | \n", + "2018-04-09 | \n", + "3.762872 | \n", + "0.112388 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "99 | \n", + "1 | \n", + "
| 2 | \n", + "2018-04-16 | \n", + "4.466967 | \n", + "0.292400 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "106 | \n", + "2 | \n", + "
| 3 | \n", + "2018-04-23 | \n", + "3.864219 | \n", + "0.071399 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "113 | \n", + "3 | \n", + "
| 4 | \n", + "2018-04-30 | \n", + "4.441625 | \n", + "0.386745 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "120 | \n", + "4 | \n", + "
<xarray.Dataset> Size: 3MB\n", + "Dimensions: (date: 179, sample: 2000)\n", + "Coordinates:\n", + " * date (date) datetime64[ns] 1kB 2018-04-02 2018-04-09 ... 2021-08-30\n", + " * sample (sample) object 16kB MultiIndex\n", + " * chain (sample) int64 16kB 0 0 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0 0 0\n", + " * draw (sample) int64 16kB 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n", + "Data variables:\n", + " y (date, sample) float64 3MB -1.121 0.559 -0.2812 ... 10.56 -2.713\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:21.486975+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1\n", + " pymc_marketing_version: 0.17.0
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<xarray.Dataset> Size: 49MB\n", + "Dimensions: (chain: 1, draw: 2000,\n", + " control: 3, date: 179,\n", + " channel: 2, fourier_mode: 4)\n", + "Coordinates:\n", + " * chain (chain) int64 8B 0\n", + " * draw (draw) int64 16kB 0 ... 1999\n", + " * control (control) <U7 84B 'event_...\n", + " * date (date) datetime64[ns] 1kB ...\n", + " * channel (channel) <U2 16B 'x1' 'x2'\n", + " * fourier_mode (fourier_mode) <U5 80B 's...\n", + "Data variables: (12/17)\n", + " y_sigma (chain, draw) float64 16kB ...\n", + " gamma_control (chain, draw, control) float64 48kB ...\n", + " yearly_seasonality_contribution (chain, draw, date) float64 3MB ...\n", + " control_contribution (chain, draw, date, control) float64 9MB ...\n", + " channel_contribution (chain, draw, date, channel) float64 6MB ...\n", + " intercept_contribution_original_scale (chain, draw) float64 16kB ...\n", + " ... ...\n", + " gamma_fourier (chain, draw, fourier_mode) float64 64kB ...\n", + " adstock_alpha (chain, draw, channel) float64 32kB ...\n", + " intercept_contribution (chain, draw) float64 16kB ...\n", + " yearly_seasonality_contribution_original_scale (chain, draw, date) float64 3MB ...\n", + " control_contribution_original_scale (chain, draw, date, control) float64 9MB ...\n", + " channel_contribution_original_scale (chain, draw, date, channel) float64 6MB ...\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:21.481861+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1\n", + " pymc_marketing_version: 0.17.0
<xarray.Dataset> Size: 3MB\n", + "Dimensions: (chain: 1, draw: 2000, date: 179)\n", + "Coordinates:\n", + " * chain (chain) int64 8B 0\n", + " * draw (draw) int64 16kB 0 1 2 3 4 5 6 ... 1994 1995 1996 1997 1998 1999\n", + " * date (date) datetime64[ns] 1kB 2018-04-02 2018-04-09 ... 2021-08-30\n", + "Data variables:\n", + " y (chain, draw, date) float64 3MB -1.121 8.656 ... -10.06 -2.713\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:21.486975+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1\n", + " pymc_marketing_version: 0.17.0
<xarray.Dataset> Size: 3kB\n", + "Dimensions: (date: 179)\n", + "Coordinates:\n", + " * date (date) datetime64[ns] 1kB 2018-04-02 2018-04-09 ... 2021-08-30\n", + "Data variables:\n", + " y (date) float64 1kB 0.4794 0.4527 0.5374 ... 0.4978 0.5388 0.5625\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:34.172099+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1
<xarray.Dataset> Size: 11kB\n", + "Dimensions: (channel: 2, date: 179, control: 3)\n", + "Coordinates:\n", + " * channel (channel) <U2 16B 'x1' 'x2'\n", + " * date (date) datetime64[ns] 1kB 2018-04-02 ... 2021-08-30\n", + " * control (control) <U7 84B 'event_1' 'event_2' 't'\n", + "Data variables:\n", + " channel_scale (channel) float64 16B 0.9967 0.9944\n", + " target_scale float64 8B 8.312\n", + " channel_data (date, channel) float64 3kB 0.3186 0.0 0.1124 ... 0.4389 0.0\n", + " target_data (date) float64 1kB 3.985 3.763 4.467 ... 4.138 4.479 4.676\n", + " control_data (date, control) float64 4kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 178.0\n", + " dayofyear (date) int32 716B 92 99 106 113 120 ... 214 221 228 235 242\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:34.173819+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1
<xarray.Dataset> Size: 11kB\n", + "Dimensions: (date_week: 179)\n", + "Coordinates:\n", + " * date_week (date_week) datetime64[ns] 1kB 2018-04-02 ... 2021-08-30\n", + "Data variables:\n", + " x1 (date_week) float64 1kB 0.3186 0.1124 0.2924 ... 0.2803 0.4389\n", + " x2 (date_week) float64 1kB 0.0 0.0 0.0 0.0 ... 0.8633 0.0 0.0 0.0\n", + " event_1 (date_week) float64 1kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n", + " event_2 (date_week) float64 1kB 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n", + " dayofyear (date_week) int32 716B 92 99 106 113 120 ... 214 221 228 235 242\n", + " t (date_week) int64 1kB 0 1 2 3 4 5 6 ... 173 174 175 176 177 178\n", + " y (date_week) float64 1kB 3.985 3.763 4.467 ... 4.138 4.479 4.676
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| \n", + " | mean | \n", + "sd | \n", + "hdi_3% | \n", + "hdi_97% | \n", + "mcse_mean | \n", + "mcse_sd | \n", + "ess_bulk | \n", + "ess_tail | \n", + "r_hat | \n", + "
|---|---|---|---|---|---|---|---|---|---|
| intercept_contribution | \n", + "0.355 | \n", + "0.014 | \n", + "0.329 | \n", + "0.379 | \n", + "0.000 | \n", + "0.000 | \n", + "1865.0 | \n", + "2295.0 | \n", + "1.0 | \n", + "
| y_sigma | \n", + "0.031 | \n", + "0.002 | \n", + "0.028 | \n", + "0.035 | \n", + "0.000 | \n", + "0.000 | \n", + "3491.0 | \n", + "3341.0 | \n", + "1.0 | \n", + "
| saturation_beta[x1] | \n", + "0.363 | \n", + "0.021 | \n", + "0.326 | \n", + "0.401 | \n", + "0.000 | \n", + "0.000 | \n", + "2061.0 | \n", + "2346.0 | \n", + "1.0 | \n", + "
| saturation_beta[x2] | \n", + "0.266 | \n", + "0.080 | \n", + "0.192 | \n", + "0.374 | \n", + "0.003 | \n", + "0.010 | \n", + "1300.0 | \n", + "1243.0 | \n", + "1.0 | \n", + "
| saturation_lam[x1] | \n", + "3.938 | \n", + "0.391 | \n", + "3.218 | \n", + "4.687 | \n", + "0.008 | \n", + "0.007 | \n", + "2435.0 | \n", + "1909.0 | \n", + "1.0 | \n", + "
| saturation_lam[x2] | \n", + "3.195 | \n", + "1.213 | \n", + "1.180 | \n", + "5.503 | \n", + "0.033 | \n", + "0.037 | \n", + "1288.0 | \n", + "1215.0 | \n", + "1.0 | \n", + "
| adstock_alpha[x1] | \n", + "0.402 | \n", + "0.031 | \n", + "0.344 | \n", + "0.458 | \n", + "0.001 | \n", + "0.000 | \n", + "2453.0 | \n", + "2416.0 | \n", + "1.0 | \n", + "
| adstock_alpha[x2] | \n", + "0.186 | \n", + "0.041 | \n", + "0.111 | \n", + "0.263 | \n", + "0.001 | \n", + "0.001 | \n", + "1623.0 | \n", + "1581.0 | \n", + "1.0 | \n", + "
| gamma_control[event_1] | \n", + "0.176 | \n", + "0.028 | \n", + "0.124 | \n", + "0.227 | \n", + "0.000 | \n", + "0.000 | \n", + "4119.0 | \n", + "2895.0 | \n", + "1.0 | \n", + "
| gamma_control[event_2] | \n", + "0.232 | \n", + "0.027 | \n", + "0.181 | \n", + "0.285 | \n", + "0.000 | \n", + "0.000 | \n", + "4094.0 | \n", + "3003.0 | \n", + "1.0 | \n", + "
| gamma_control[t] | \n", + "0.001 | \n", + "0.000 | \n", + "0.001 | \n", + "0.001 | \n", + "0.000 | \n", + "0.000 | \n", + "2901.0 | \n", + "2619.0 | \n", + "1.0 | \n", + "
| gamma_fourier[sin_1] | \n", + "0.003 | \n", + "0.003 | \n", + "-0.004 | \n", + "0.010 | \n", + "0.000 | \n", + "0.000 | \n", + "3491.0 | \n", + "2962.0 | \n", + "1.0 | \n", + "
| gamma_fourier[sin_2] | \n", + "-0.058 | \n", + "0.003 | \n", + "-0.064 | \n", + "-0.051 | \n", + "0.000 | \n", + "0.000 | \n", + "3504.0 | \n", + "3224.0 | \n", + "1.0 | \n", + "
| gamma_fourier[cos_1] | \n", + "0.062 | \n", + "0.003 | \n", + "0.056 | \n", + "0.068 | \n", + "0.000 | \n", + "0.000 | \n", + "3539.0 | \n", + "2600.0 | \n", + "1.0 | \n", + "
| gamma_fourier[cos_2] | \n", + "0.001 | \n", + "0.004 | \n", + "-0.006 | \n", + "0.008 | \n", + "0.000 | \n", + "0.000 | \n", + "3685.0 | \n", + "2698.0 | \n", + "1.0 | \n", + "
<xarray.Dataset> Size: 12MB\n", + "Dimensions: (date: 179, sample: 4000)\n", + "Coordinates:\n", + " * date (date) datetime64[ns] 1kB 2018-04-02 ... 2021-08-30\n", + " * sample (sample) object 32kB MultiIndex\n", + " * chain (sample) int64 32kB 0 0 0 0 0 0 0 0 0 ... 3 3 3 3 3 3 3 3\n", + " * draw (sample) int64 32kB 0 1 2 3 4 5 ... 995 996 997 998 999\n", + "Data variables:\n", + " y (date, sample) float64 6MB 0.5806 0.5062 ... 0.5605 0.6118\n", + " y_original_scale (date, sample) float64 6MB 4.826 4.208 ... 4.659 5.085\n", + "Attributes:\n", + " created_at: 2025-11-02T22:06:36.629721+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1
| \n", + " | date | \n", + "intercept | \n", + "channel__x1 | \n", + "channel__x2 | \n", + "control__event_1 | \n", + "control__event_2 | \n", + "control__t | \n", + "yearly_seasonality | \n", + "
|---|---|---|---|---|---|---|---|---|
| 0 | \n", + "2018-04-02 | \n", + "2.95057 | \n", + "1.078479 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "0.000000 | \n", + "0.022348 | \n", + "
| 1 | \n", + "2018-04-09 | \n", + "2.95057 | \n", + "0.829539 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "0.005135 | \n", + "0.074449 | \n", + "
| 2 | \n", + "2018-04-16 | \n", + "2.95057 | \n", + "1.288929 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "0.010271 | \n", + "0.120304 | \n", + "
| 3 | \n", + "2018-04-23 | \n", + "2.95057 | \n", + "0.788845 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "0.015406 | \n", + "0.154603 | \n", + "
| 4 | \n", + "2018-04-30 | \n", + "2.95057 | \n", + "1.534806 | \n", + "0.0 | \n", + "0.0 | \n", + "0.0 | \n", + "0.020542 | \n", + "0.172772 | \n", + "
| \n", + " | date_week | \n", + "x1 | \n", + "x2 | \n", + "event_1 | \n", + "event_2 | \n", + "t | \n", + "
|---|---|---|---|---|---|---|
| 0 | \n", + "2021-09-06 | \n", + "0.438857 | \n", + "0.0 | \n", + "0 | \n", + "0 | \n", + "179 | \n", + "
| 1 | \n", + "2021-09-13 | \n", + "0.438857 | \n", + "0.0 | \n", + "0 | \n", + "0 | \n", + "180 | \n", + "
| 2 | \n", + "2021-09-20 | \n", + "0.438857 | \n", + "0.0 | \n", + "0 | \n", + "0 | \n", + "181 | \n", + "
| 3 | \n", + "2021-09-27 | \n", + "0.438857 | \n", + "0.0 | \n", + "0 | \n", + "0 | \n", + "182 | \n", + "
| 4 | \n", + "2021-10-04 | \n", + "0.438857 | \n", + "0.0 | \n", + "0 | \n", + "0 | \n", + "183 | \n", + "
<xarray.Dataset> Size: 576kB\n", + "Dimensions: (date: 5, sample: 4000, channel: 2)\n", + "Coordinates:\n", + " * date (date) datetime64[ns] 40B 2021-09-06...\n", + " * sample (sample) object 32kB MultiIndex\n", + " * channel (channel) <U2 16B 'x1' 'x2'\n", + " * chain (sample) int64 32kB 0 0 0 0 ... 3 3 3 3\n", + " * draw (sample) int64 32kB 0 1 2 ... 998 999\n", + "Data variables:\n", + " y_original_scale (date, sample) float64 160kB 4.959 ....\n", + " channel_contribution_original_scale (date, channel, sample) float64 320kB ...\n", + "Attributes:\n", + " created_at: 2025-11-02T22:07:13.943832+00:00\n", + " arviz_version: 0.22.0\n", + " inference_library: pymc\n", + " inference_library_version: 5.25.1