Index A | B | C | D | E | F | G | H | I | J | L | M | N | P | Q | R | S | T | U | V | W | X | Y A AverageComparison (class in multiple_inference.confidence_set) B BaselineComparison (class in multiple_inference.confidence_set) BayesBase (class in multiple_inference.bayes.base) BayesResults (class in multiple_inference.bayes.base) bounds (multiple_inference.stats.quantile_unbiased attribute) C compute_best_params() (multiple_inference.bayes.base.BayesResults method) (multiple_inference.confidence_set.SimultaneousRankingResults method) compute_robust_critical_value() (in module multiple_inference.bayes.normal) conf_int() (multiple_inference.base.ResultsBase method) (multiple_inference.bayes.normal.NormalResults method) ConfidenceSet (class in multiple_inference.confidence_set) ConfidenceSetResults (class in multiple_inference.confidence_set) cov (multiple_inference.base.ModelBase attribute) D distributions (multiple_inference.bayes.base.BayesResults attribute) (multiple_inference.stats.mixture attribute) dx (multiple_inference.stats.quantile_unbiased attribute) E endog_names (multiple_inference.base.ModelBase attribute) exog_names (multiple_inference.base.ModelBase attribute) expected_wasserstein_distance() (in module multiple_inference.utils) (multiple_inference.bayes.base.BayesResults method) F fit() (multiple_inference.base.ModelBase method) from_csv() (multiple_inference.base.ModelBase class method) from_results() (multiple_inference.base.ModelBase class method) G get_index() (multiple_inference.base.ModelBase method) get_indices() (multiple_inference.base.ModelBase method) get_joint_distribution() (multiple_inference.bayes.base.BayesBase method) get_joint_prior() (multiple_inference.bayes.base.BayesBase method) get_marginal_distribution() (multiple_inference.bayes.base.BayesBase method) (multiple_inference.rank_condition.RankCondition method) (multiple_inference.significance_condition.SignificanceCondition method) get_marginal_prior() (multiple_inference.bayes.base.BayesBase method) H holm_bonferroni_correction() (in module multiple_inference.utils) hypothesis_heatmap() (multiple_inference.confidence_set.PairwiseComparisonResults method) I Improper (class in multiple_inference.bayes.improper) interval_masses (multiple_inference.stats.truncnorm attribute) J joint_distribution (class in multiple_inference.stats) L likelihood() (multiple_inference.bayes.base.BayesResults method) line_plot() (multiple_inference.bayes.base.BayesResults method) (multiple_inference.bayes.nonparametric.NonparametricResults method) loc (multiple_inference.stats.truncnorm attribute) logpdf() (multiple_inference.stats.joint_distribution method) lower_bound (multiple_inference.stats.truncnorm attribute) M MarginalRanking (class in multiple_inference.confidence_set) MarginalRankingResults (class in multiple_inference.confidence_set) mean (multiple_inference.base.ModelBase attribute) mean() (multiple_inference.stats.mixture method) mixture (class in multiple_inference.stats) ModelBase (class in multiple_inference.base) module multiple_inference.base multiple_inference.bayes.base multiple_inference.bayes.improper multiple_inference.bayes.nonparametric multiple_inference.bayes.normal multiple_inference.confidence_set multiple_inference.rank_condition multiple_inference.significance_condition multiple_inference.stats multiple_inference.utils multiple_inference.base module multiple_inference.bayes.base module multiple_inference.bayes.improper module multiple_inference.bayes.nonparametric module multiple_inference.bayes.normal module multiple_inference.confidence_set module multiple_inference.rank_condition module multiple_inference.significance_condition module multiple_inference.stats module multiple_inference.utils module multivariate_distribution (multiple_inference.bayes.base.BayesResults attribute) N n_params (multiple_inference.base.ModelBase attribute) n_samples (multiple_inference.stats.truncnorm attribute) Nonparametric (class in multiple_inference.bayes.nonparametric) NonparametricResults (class in multiple_inference.bayes.nonparametric) Normal (class in multiple_inference.bayes.normal) NormalResults (class in multiple_inference.bayes.normal) P PairwiseComparison (class in multiple_inference.confidence_set) PairwiseComparisonResults (class in multiple_inference.confidence_set) pdf() (multiple_inference.stats.joint_distribution method) point_plot() (multiple_inference.base.ResultsBase method) ppf() (multiple_inference.stats.quantile_unbiased method) Q quantile_unbiased (class in multiple_inference.stats) R rank_conf_int() (multiple_inference.bayes.base.BayesResults method) rank_df (multiple_inference.bayes.base.BayesResults attribute) rank_matrix_plot() (multiple_inference.bayes.base.BayesResults method) rank_point_plot() (multiple_inference.bayes.base.BayesResults method) RankCondition (class in multiple_inference.rank_condition) RankConditionResults (class in multiple_inference.rank_condition) reconstruction_point_plot() (multiple_inference.bayes.base.BayesResults method) ResultsBase (class in multiple_inference.base) rvs() (multiple_inference.stats.joint_distribution method) S save() (multiple_inference.base.ResultsBase method) scale (multiple_inference.stats.truncnorm attribute) seed (multiple_inference.base.ModelBase attribute) SignificanceCondition (class in multiple_inference.significance_condition) SignificanceConditionResults (class in multiple_inference.significance_condition) SimultaneousRanking (class in multiple_inference.confidence_set) SimultaneousRankingResults (class in multiple_inference.confidence_set) std() (multiple_inference.stats.mixture method) summary() (multiple_inference.base.ResultsBase method) T test_hypotheses() (multiple_inference.confidence_set.ConfidenceSetResults method) (multiple_inference.confidence_set.PairwiseComparisonResults method) to_csv() (multiple_inference.base.ModelBase method) truncnorm (class in multiple_inference.stats) truncnorm_kwargs (multiple_inference.stats.quantile_unbiased attribute) U upper_bound (multiple_inference.stats.truncnorm attribute) V var() (multiple_inference.stats.mixture method) W weighted_quantile() (in module multiple_inference.utils) weights (multiple_inference.stats.mixture attribute) X X (multiple_inference.base.ModelBase attribute) Y y (multiple_inference.stats.quantile_unbiased attribute)