Negative delta x causes sampling error

[wd60622]

Default implementation uses Gamma distribution which doesn't work well with delta x (and delta y) being negative.

Absolute value of the difference and delta_y could fix. Location of change: https://github.com/pymc-labs/pymc-marketing/blob/78964f0708179da63080a7d5c0398433616f774c/pymc_marketing/mmm/lift_test.py#L278-L287

Reproducible example:

import numpy as np
import pandas as pd

from pymc_marketing.mmm import DelayedSaturatedMMM

data_url = "https://raw.githubusercontent.com/pymc-labs/pymc-marketing/main/data/mmm_example.csv"
data = pd.read_csv(data_url, parse_dates=["date_week"])

mmm = DelayedSaturatedMMM(
    date_column="date_week",
    channel_columns=["x1", "x2"],
    control_columns=[
        "event_1",
        "event_2",
        "t",
    ],
    adstock_max_lag=8,
    yearly_seasonality=2,
)

# Set features and target
X = data.drop("y", axis=1)
y = data["y"]

mmm.build_model(X, y)

# Delta x is negative 
df_lift_test = pd.DataFrame({
    "channel": ["x1"], 
    "x": [1], 
    "delta_x": [-0.1], 
    "delta_y": [-0.1], 
    "sigma": [0.05], 
})
mmm.add_lift_test_measurements(df_lift_test)
mmm.fit(X, y)