Generalized Pivotal Quantity Inference for the Youden Index

Documentation for package ‘gpqyouden’ version 0.1.0

calculate_mu1_for_dataframe	Compute mu_1 for each row of a parameter data frame
default_param_grid	Build the default parameter grid used in Lai et al. (2012)
dmixnorm	Density of the contaminated normal mixture
eq.J2	Equation whose root gives mu_1
find_mu1_from_J2	Find mu_1 from the Youden index under the normal model
find_mu1_from_J_mixture	Find mu_1 from the Youden index under the mixture model
generate_mixture_sample	Generate a sample from the contaminated normal mixture
generate_mixture_tables	Generate LaTeX tables for the mixture model simulation
generate_normal_tables	Generate LaTeX tables for the normal model simulation
generate_param_grid	Build a custom parameter grid
gpq_c	GPQ for the optimal cut-point
gpq_from_sample	Generate generalized pivotal quantities for one simulated sample
gpq_J	GPQ for the Youden index
gpq_mu	GPQ for the mean
gpq_sigma	GPQ for the standard deviation
J2.theoretical	Theoretical Youden index under the normal model
J_true_mixture	True Youden index and optimal cut-point under the mixture model
mix_sd	Standard deviations of the two mixture components
pmixnorm	CDF of the contaminated normal mixture
run_one_row	Run the simulation for a single row of the parameter grid
run_parallel_grid	Run the simulation in parallel, detecting the OS automatically
run_simulation	Run the Monte Carlo simulation for a single parameter scenario