get_banocc_output: Takes a model fit from BAnOCC, evaluates convergence and...
In banocc: Bayesian ANalysis Of Compositional Covariance

Description Usage Arguments Value See Also Examples

Takes a model fit from BAnOCC, evaluates convergence and generates appropriate convergence metrics and inference

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get_banocc_output(banoccfit, conf_alpha = 0.05, get_min_width = FALSE,
  calc_snc = TRUE, eval_convergence = TRUE, verbose = FALSE,
  num_level = 0)

`banoccfit`	Either a `stanfit` object (the `Fit` element returned by `run_banocc`), or the list returned by a call to `run_banocc`.
`conf_alpha`	The percentage of the posterior density outside the credible interval. That is, a `1-conf_alpha` * 100% credible interval will be returned.
`get_min_width`	A boolean value: should the minimum CI width that includes zero be calculated?
`calc_snc`	Boolean: should the scaled neighborhood criterion be calculated?
`eval_convergence`	Boolean: if 'TRUE', convergence will be evaluated using the Rhat statistic, and the fit output (estimates, credible intervals, etc.) will be missing if this statistic does not indicate convergence.
`verbose`	Print informative statements as the function executes?
`num_level`	The number of indentations to add to the output when `verbose = TRUE`.

Returns a named list with the following elements:

CI: The 1-conf_alpha * 100% credible intervals
Estimates.median: The correlation estimates, which are the marginal posterior medians
Min.width: Only present if the get_min_width argument is TRUE. The minimum CI width that includes zero for each correlation.
SNC: Only present if the calc_snc argument is TRUE. The scaled neighborhood criterion for each correlation.
Fit: The stanfit object returned by the call to run_banocc.
Data: Only present if the banoccfit argument is specified as the output of a call to run_banocc. It will be missing if banoccfit is specified as a stanfit object.

vignette("banocc-vignette") for more examples.

data(compositions_null)
  ## Not run: 
    compiled_banocc_model <- rstan::stan_model(model_code=banocc_model)
    b_fit <- run_banocc(C=compositions_null,
                            compiled_banocc_model=compiled_banocc_model)
    b_output <- get_banocc_output(banoccfit=b_fit)
  
## End(Not run)