liesel.goose.summary_m

Posterior statistics and diagnostics.

Functions

add_hdi(arviz_array, subparam_stats, ...)	Add Highest Density Intervals to dictionary which collects all summary statistics and diagnostics for one specific subparameter (e.g.
add_num_effective(arviz_array, round_digits)	Compute the effective sample size of one specific subparameter (e.g.
add_quantiles(subparam_chains, ...)	Add posterior quantiles to dictionary which collects all summary statistics and diagnostics for one specific subparameter (e.g.
add_rhat(arviz_array, round_digits)	Compute a single Rhat value for multiple chains of the same subparameter.
adjust_dimensions(param_chains, num_dim)	Make shape of posterior samples for one dimensional parameters (e.g.
collect_param_dfs(posterior_samples, ...)	Combine data frames with summary statistics and diagnostics of all model parameters into a single DataFrame.
collect_param_dicts(posterior_samples, ...)	Combine dictionaries with summary statistics and diagnostics of all model parameters into a single dictionary.
collect_subparam_dfs(param_chains, ...)	Combine data frames with summary statistics and diagnostics within one parameter vector (e.g.
collect_subparam_dicts(param_chains, ...)	Combine dictionaries with summary statistics and diagnostics within one parameter vector (e.g.
combine_chains(subparam_chains)	Concatenate all separate chains to a single chain for multi-chain sampling.
compute_hdi(arviz_array, hdi_prob, round_digits)	Compute Highest-Density Intervals for all chains.
compute_quantiles(subparam_chains, ...)	Compute posterior quantiles of one specific subparameter (e.g.
compute_single_hdi(arviz_subarray, hdi_prob, ...)	Compute Highest-Density Interval for a single chain.
get_param_stats(param, posterior_samples, ...)	Collect all summary statistics and diagnostics for one specific parameter vector (e.g.
get_subparam_stats(subparam_chains, ...)	Collect all summary statistics and diagnostics for one specific subparameter (e.g.
move_col_first(df, colname)	Move last column of a DataFrame to the first column.
numpy_to_arviz(subparam_chains)	Convert data structure of arviz package to numpy array.
raise_chain_indices_error(chain_indices, ...)	Display informative error message with valid chain_indices inputs.
raise_dimension_error(param, num_dim)	Check for correct array dimensions of posterior samples.
raise_param_indices_error(param_indices, ...)	Display informative error message with valid param_indices inputs for this specific param.
subparam_stats_to_df(subparam_stats, per_chain)	Convert dictionary which collects all summary statistics and diagnostics for one specific subparameter (e.g.
summary(results[, per_chain, params, ...])	Compute summary statistics and diagnostic measures of posterior samples.
validate_chain_indices(chain_indices, ...)	Convert int or None input of chain_indices to sequence of integers.
validate_param_indices(param_indices, ...)	Convert int or None input of param_indices to sequence of integers.
validate_params(posterior_samples, params)	Convert str or None input of params to sequence of strings.

Classes

ErrorSummaryForOneCode(error_code, ...)
Summary(results[, additional_chain, ...])	A summary object.