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Библиотека для расчета минимального определяемого эффекта (MDE) в A/B тестах.

Project description

medoed

medoed

Библиотека для расчета минимального определяемого эффекта (MDE) в A/B тестах.

Установка

pip install medoed

Пример использования

from medoed import MDECalculator

mde_calculator = MDECalculator(
    pre_experiment_data=pre_experiment_data,
    date_field='install_date',
    metrics=['revenue', 'retention'],
    historical_data=historical_data,
    strata=['geo', 'platform'],
    alpha=0.05,
    power=0.8,
    outliers_handling_method='replace_threshold',
    outliers_threshold_quantile=0.995,
    outlier_type='upper',
    test_days=30,
    sample_size=10000,
    are_correction=True,
    continuous_alternative='two-sided'
)

df_mde = mde_calculator.calculate(n_processes=8)
df_mde

Требования

  • Python 3.8+
  • pandas 1.3+
  • numpy 1.20+
  • scipy 1.7+
  • statsmodels 0.13+
  • otvertka 0.1.10+
  • tqdm 4.65+

Лицензия

MIT

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