credint: Posterior Quantiles

In EMC2: Bayesian Hierarchical Analysis of Cognitive Models of Choice

Posterior Quantiles

Description

Returns the quantiles of the selected parameter type. Full range of possible samples manipulations described in get_pars.

Usage

## S3 method for class 'emc.prior'
credint(
  x,
  selection = "mu",
  probs = c(0.025, 0.5, 0.975),
  digits = 3,
  N = 1000,
  covariates = NULL,
  ...
)

## S3 method for class 'emc'
credint(x, selection = "mu", probs = c(0.025, 0.5, 0.975), digits = 3, ...)

credint(x, ...)

Arguments

x	An emc or emc.prior object
selection	A Character vector. Indicates which parameter types to check (e.g., alpha, mu, sigma2, correlation).
probs	A vector. Indicates which quantiles to return from the posterior.
digits	Integer. How many digits to round the output to
N	An integer. Number of samples to use for the quantile calculation (only for prior.emc objects)
covariates	A list of covariates to use for the quantile calculation (only for prior.emc objects)
...	Optional additional arguments that can be passed to get_pars

Value

A list of posterior quantiles for each parameter group in the selected parameter type.

Examples

credint(samples_LNR)

EMC2 documentation built on April 11, 2025, 5:50 p.m.