BayesTools_ensemble_tables {BayesTools} | R Documentation |

Creates estimate summaries based on posterior distributions created by mix_posteriors, inference summaries based on inference created by ensemble_inference, or ensemble summary/diagnostics based on a list of models_inference models (or marginal_inference in case of marginal_estimates_table).

```
ensemble_estimates_table(
samples,
parameters,
probs = c(0.025, 0.95),
title = NULL,
footnotes = NULL,
warnings = NULL,
transform_factors = FALSE,
transform_orthonormal = FALSE,
formula_prefix = TRUE
)
ensemble_inference_table(
inference,
parameters,
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL
)
ensemble_summary_table(
models,
parameters,
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL,
remove_spike_0 = TRUE,
short_name = FALSE
)
ensemble_diagnostics_table(
models,
parameters,
title = NULL,
footnotes = NULL,
warnings = NULL,
remove_spike_0 = TRUE,
short_name = FALSE
)
ensemble_estimates_empty_table(
probs = c(0.025, 0.95),
title = NULL,
footnotes = NULL,
warnings = NULL
)
ensemble_inference_empty_table(title = NULL, footnotes = NULL, warnings = NULL)
ensemble_summary_empty_table(title = NULL, footnotes = NULL, warnings = NULL)
ensemble_diagnostics_empty_table(
title = NULL,
footnotes = NULL,
warnings = NULL
)
marginal_estimates_table(
samples,
inference,
parameters,
probs = c(0.025, 0.95),
logBF = FALSE,
BF01 = FALSE,
title = NULL,
footnotes = NULL,
warnings = NULL,
formula_prefix = TRUE
)
```

`samples` |
posterior samples created by mix_posteriors |

`parameters` |
character vector of parameters (or a named list with of character vectors for summary and diagnostics tables) specifying the parameters (and their grouping) for the summary table |

`probs` |
quantiles for parameter estimates |

`title` |
title to be added to the table |

`footnotes` |
footnotes to be added to the table |

`warnings` |
warnings to be added to the table |

`transform_factors` |
whether factors with orthonormal/meandif prior distribution should be transformed to differences from the grand mean |

`transform_orthonormal` |
(to be depreciated) whether factors with orthonormal prior distributions should be transformed to differences from the grand mean |

`formula_prefix` |
whether the parameter prefix from formula should
be printed. Defaults to |

`inference` |
model inference created by ensemble_inference |

`logBF` |
whether the Bayes factor should be on log scale |

`BF01` |
whether the Bayes factor should be inverted |

`models` |
list of models_inference model objects,
each of which containing a list of |

`remove_spike_0` |
whether prior distributions equal to spike
at 0 should be removed from the |

`short_name` |
whether the prior distribution names should be
shortened. Defaults to |

`ensemble_estimates_table`

returns a table with the
model-averaged estimates, `ensemble_inference_table`

returns
a table with the prior and posterior probabilities and inclusion
Bayes factors, `ensemble_summary_table`

returns a table with
overview of the models included in the ensemble, and
`ensemble_diagnostics_table`

returns an overview of the MCMC
diagnostics for the models included in the ensemble. All of the
tables are objects of class 'BayesTools_table'.

ensemble_inference mix_posteriors BayesTools_model_tables

[Package *BayesTools* version 0.2.16 Index]