R: Optimal Diagnostic Cutoff Selection under Scale Mixtures of Skew-Normal Distributions

# Optimal Diagnostic Cutoff Selection under Scale Mixtures of Skew-Normal Distributions

## Documentation for package ‘smsncut’ version 0.1.0

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

cutoff_admissible_interval | Construct the admissible interval [a, b]
cutoff_boundary_check | Verify boundary conditions of Proposition 5.7
cutoff_build_interval | Build a padded search interval for cutoff root-finding
cutoff_ci | Wald confidence interval for the optimal cutoff
cutoff_expand_interval_until_valid | Expand the search interval until boundary conditions hold
cutoff_identifiability | Local identifiability diagnostic
cutoff_optimal | Optimal diagnostic cutoff under SMSN distributions
cutoff_phi | Estimating equation phi(c, theta)
cutoff_risk | Weighted misclassification risk
cutoff_variance | Asymptotic variance of the plug-in cutoff estimator
cutoff_youden | Parametric Youden cutoff under SMSN distributions
mc_one_rep | Run one Monte Carlo replication
mc_run_all | Run all scenarios
mc_simulate_scenario | Monte Carlo simulation for one scenario
smsn_auc | Plug-in AUC estimator under SMSN distributions
smsn_cdf | CDF of an SMSN distribution
smsn_density | Density of an SMSN distribution
smsn_fit | Fit an SMSN model by maximum likelihood
smsn_quantile | Quantile function of an SMSN distribution
smsn_rdist | Random generation from an SMSN distribution
smsn_roc | Parametric ROC curve under SMSN distributions