sccoda.util.result_classes.CAResult.complete_beta_df¶
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CAResult.
complete_beta_df
(intercept_df, effect_df, target_fdr=0.05)¶ Evaluation of MCMC results for effect parameters. This function is only used within self.summary_prepare. This function also calculates the posterior inclusion probability for each effect and decides whether effects are significant.
- Parameters
- Return type
- Returns
effect DataFrame
effect_df – DataFrame with inclusion probability, final parameters, expected sample