calc_relative_var: Calculate jack-knife Monte Carlo SE for variance estimators

In simhelpers: Helper Functions for Simulation Studies

Calculate jack-knife Monte Carlo SE for variance estimators

Description

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.

Usage

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)

simhelpers documentation built on May 4, 2022, 1:05 a.m.