TrimmedMean.rho()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.norms.TrimmedMean.rho TrimmedMean.rho(z)

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RLMResults.summary2()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLMResults.summary2

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static RLMResults.bse()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLMResults.bse

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robust.scale.mad()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.scale.mad statsmodels.robust.scale.mad(a, c=0.67448975019608171, axis=0

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RLMResults.wald_test()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLMResults.wald_test

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RobustNorm.rho()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.norms.RobustNorm.rho RobustNorm.rho(z)

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static RLMResults.pvalues()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLMResults.pvalues

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RLM.from_formula()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLM.from_formula

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robust.scale.stand_mad()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.scale.stand_mad statsmodels.robust.scale.stand_mad(a, c=0

2025-01-10 15:47:30
RLMResults.load()
  • References/Python/Statsmodels/Robust Linear Models

statsmodels.robust.robust_linear_model.RLMResults.load

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