Credible intervals for the fixed effects

Usage

# S3 method for class 'tulpa_fit'
confint(object, parm = NULL, level = 0.95, ...)

Arguments

object: A tulpa_fit object.
parm: Parameter names or indices (default: all fixed effects). Indices address the fixed effects. A name that is not a fixed effect is read off the fit's posterior draws when they carry a column of that name (for example a sampler's log_sigma_re), as their equal-tailed quantile interval; any other name is an error.
level: Interval level, a single number in (0, 1) (default 0.95).
...: Ignored.

Value

Matrix with lower and upper columns, labelled as stats::confint.default() labels them ("2.5 %" and "97.5 %" at the default level). A nested-Laplace fit carries interval_source / interval_declined (which read produced the bounds – by default the grid's Gaussian-mixture CDF), retained_mass (the share of the grid weight the bounds are conditional on), and skew_applied, one logical per reported coefficient saying whether its bounds are the inner-Laplace skew-corrected quantiles or not. See summary.tulpa_fit().