tasccoda.tree_results.CAResult_tree

class tasccoda.tree_results.CAResult_tree(sampling_stats, model_specs, **kwargs)

Result class for tascCODA, extends the arviz framework for inference data.

The CAResult_tree class is an extension of az.InferenceData, that adds some information about the compositional model and is able to print humanly readable results. It supports all functionality from az.InferenceData.

Attributes

attrs

Attributes of InferenceData object.

Methods

complete_alpha_df(intercept_df)	Evaluation of MCMC results for intercepts.
complete_beta_df(intercept_df, effect_df, …)	Evaluation of MCMC results for feature-level effect parameters.
complete_node_df(node_df)	Evaluation of MCMC results for node-level effect parameters.
draw_tree_effects(tree, covariate, *args, …)	Plot a tree with colored circles on the nodes indicating significant effects.
get_significant_results(*args, **kwargs)	Returns credible (nonzero effect) node-level names and feature-level tree indices
summary(*args, **kwargs)	Printing method for tascCODA’s summary.
summary_extended(*args, **kwargs)	Extended (diagnostic) printing function that shows more info about the sampling result
summary_prepare(*args, **kwargs)	Generates summary dataframes for intercepts and slopes.