Autocorrelation Function Plots for koma_estimate Objects

Visualize autocorrelation functions (ACF) for coefficient draws from a koma_estimate object. By default, beta, gamma, and sigma draws are shown when available.

Usage

acf_plot(x, ...)

Arguments

x

A koma_estimate object.

...

Additional arguments controlling the plot. See Details.

Value

A ggplot object, or a plotly object when interactive = TRUE and plotly is available.

Details

Additional arguments supported in ...:

variables

Optional character vector of endogenous variables to plot.

params

Optional character vector of parameter groups to plot (e.g., "beta", "gamma", "sigma"). Defaults to all available.

thin

Optional integer thinning interval for the stored draws. Default is 1 (no thinning).

max_draws

Optional integer cap on the number of draws used per ACF. When set, the most recent draws are kept.

max_lag

Optional integer maximum lag for ACF computation. When NULL, defaults to min(30, n_draws - 1) per series.

conf_level

Optional numeric confidence level in (0, 1) used for ACF significance bands. Default is 0.95.

scales

Facet scale option passed to ggplot2::facet_wrap. Default is "fixed".

facet_ncol

Optional integer number of columns for facets.

interactive

Logical. If TRUE and plotly is available, return an interactive plot via plotly::ggplotly. Default is FALSE.

ACF values are computed with stats::acf(..., plot = FALSE) for each retained coefficient draw series.

Note: sigma plots use omega_tilde_jw and show only variances (no covariances) from each covariance draw.

The red dashed horizontal lines show approximate significance bounds \(\pm z_{1-\alpha/2}/\sqrt{n}\) for zero autocorrelation, where \(\alpha = 1 - \code{conf_level}\) and \(n\) is the number of retained draws for the corresponding coefficient series.