test.control: Control function for the adaptive norm test
In adam-s-elder/amar: Statistical Test for the Multivariate Point Null Hypotheses

Control function for the adaptive norm test

test.control(
  n_mc_samples = 300,
  nrm_type = "lp",
  perf_meas = "est_acc",
  pos_lp_norms = c(1, 2, 3, "max"),
  show_hist = FALSE,
  ld_est_meth = "par_boot",
  ts_ld_bs_samp = 250,
  more_info = TRUE,
  ret_cov_mat = FALSE,
  ...
)

`n_mc_samples`	Number of samples to be used in estimating the limiting distribution of the test statistic under the null.
`nrm_type`	The type of norm to be used for the test. Generally the l_p norm
`perf_meas`	the prefered measure used to generate the test statistic.
`pos_lp_norms`	The index of the norms to be considered. For example if we use the l_p norm, norms_indx specifies the different p's to try.
`show_hist`	set to True to see a histogram of the test statistic's limiting distribution MC draws compared to the estimated parameter.
`ld_est_meth`	String indicating method for estimating the limiting distribution of the test statistic parametric bootstrap or permutation.
`ts_ld_bs_samp`	The number of test statistic limiting distribution bootstrap samples to be drawn.
`more_info`	Boolean indicating if the function should return more information that just the p-value. When true, the chosen norm index, the bonferroni based p-value, the test statistic, and the estimated distribution of the test statistic will be returned.
`ret_cov_mat`	Boolean indicating if the function should also return the estimated covariance matrix. This can somewhat slow computation and result in large file sizes at higher dimensions. The argument 'more_info' must be set to 'TRUE' for this option to be possible.
`...`	Other arguments needed in other places.