Calculates relative bias, mean squared error (relative mse), and root mean squared error (relative rmse) of variance estimators. The function also calculates the associated jack-knife Monte Carlo standard errors.

calc_relative_var(
  res_dat,
  estimates,
  var_estimates,
  perfm_criteria = c("relative bias", "relative mse", "relative rmse")
)

Arguments

res_dat

data frame or tibble containing the simulation results.

estimates

name of the column containing the estimates.

var_estimates

name of the column containing the variance estimates.

perfm_criteria

character or character vector indicating the performance criteria to be calculated.

Value

A tibble containing the number of simulation iterations, performance criteria estimate(s) and the associated MCSE.

Examples

calc_relative_var(res_dat = alpha_res, estimates = A, var_estimates = Var_A)
#> # A tibble: 1 x 7 #> K rel_bias_var rel_bias_var_mc… rel_mse_var rel_mse_var_mcse rel_rmse_var #> <int> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 1000 0.440 0.101 0.726 0.337 0.852 #> # … with 1 more variable: rel_rmse_var_mcse <dbl>