BvM diagnostic for the mean functional under a DP prior. — morie_ghosal_bernstein_von_mises • rmorie

BvM diagnostic for the mean functional under a DP prior.

Usage

morie_ghosal_bernstein_von_mises(
  x,
  theta0 = NULL,
  B = 500,
  seed = 0,
  deterministic_seed = NULL
)

Arguments

x: Numeric data vector.
theta0: Optional null value for the mean functional.
B: Integer number of bootstrap draws (default 500).
seed: Integer RNG seed (default 0).
deterministic_seed: Optional integer; if supplied, RNG state is derived via morie_det_rng() keyed on ("ghbvm", deterministic_seed) so Py<->R streams agree on the canonical fixture. When NULL (default) behaviour is unchanged.

Value

Named list with estimate, se, theta_hat, z_ks_stat, z_ks_pvalue, wald, wald_pvalue, n, B, method.

Examples

morie_ghosal_bernstein_von_mises(x = rnorm(50))
#> $estimate
#> [1] 0.02925501
#> 
#> $se
#> [1] 0.1195717
#> 
#> $theta_hat
#> [1] 0.02393097
#> 
#> $z_ks_stat
#> [1] 0.04385294
#> 
#> $z_ks_pvalue
#> [1] 0.2914242
#> 
#> $wald
#> [1] NA
#> 
#> $wald_pvalue
#> [1] NA
#> 
#> $n
#> [1] 50
#> 
#> $B
#> [1] 500
#> 
#> $method
#> [1] "BvM for mean functional (Bayesian bootstrap)"
#>