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Running Means for koma_estimate Objects

Source: R/running_mean.R
running_mean.Rd

Compute running means (cumulative averages) for coefficient draws from a koma_estimate object. By default, beta, gamma, and sigma draws are included when available.

Usage

running_mean(x, ...)

Arguments

x

A koma_estimate object.

...

Additional arguments controlling the output. See Details.

Value

A data.frame with columns draw, value, variable, param, coef, draw_position, in_grace_window, and label.

Details

Additional arguments supported in ...:

variables

Optional character vector of endogenous variables to include.

params

Optional character vector of parameter groups to include (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 returned. When set, the most recent draws are kept.

grace_draws

Optional integer number of initial retained draws to flag as a grace window for convergence interpretation. If NULL, defaults to max(50, ceiling(0.1 * n_retained)) per series.

Note: sigma values are based on omega_tilde_jw and use only variances (no covariances) from each covariance draw.

Examples

data("simulated_sem")
set.seed(11)

fit <- estimate(
  ts_data = simulated_sem$ts_data,
  sys_eq = simulated_sem$sys_eq,
  dates = simulated_sem$dates,
  options = list(gibbs = list(ndraws = 10))
)
#> 
#> ── Gibbs Sampler Settings ──────────────────────────────────────────────────────
#> 
#> ── System Wide Settings ──
#>   • Number of draws (`ndraws`): 10
#>   • Burn-in ratio (`burnin_ratio`): 0.5
#>   • Burn-in (`burnin`): 5
#>   • Store frequency (`nstore`): 1
#>   • Number of saved draws (`nsave`): 5
#>   • Tau (`tau`): 1.1
#> 
#> 
#> ── Estimation ──────────────────────────────────────────────────────────────────
rm_df <- running_mean(fit, params = "beta", max_draws = 100)
head(rm_df)
#>   draw     value    variable param             coef draw_position
#> 1    1 1.0786305 consumption  beta         constant             1
#> 2    1 0.4568034 consumption  beta consumption.L(1)             1
#> 3    1 0.2709837 consumption  beta consumption.L(2)             1
#> 4    2 1.1079817 consumption  beta         constant             2
#> 5    2 0.5100500 consumption  beta consumption.L(1)             2
#> 6    2 0.2207444 consumption  beta consumption.L(2)             2
#>   in_grace_window                             label
#> 1            TRUE         consumption:beta:constant
#> 2            TRUE consumption:beta:consumption.L(1)
#> 3            TRUE consumption:beta:consumption.L(2)
#> 4            TRUE         consumption:beta:constant
#> 5            TRUE consumption:beta:consumption.L(1)
#> 6            TRUE consumption:beta:consumption.L(2)