acc_sim                 Utility function to generate accuracy metrics,
                        for use with 'estimate_accuracy()'
conduct_interpolation   Conduct interpolation on a single simulation
create_scb_model        Create custom model fitting function
create_scb_prediction   Create custom prediction function
estimate_accuracy       Estimate sample complexity bounds for a binary
                        classification algorithm using either simulated
                        or user-supplied data.
fit_and_predict         Fit an extrapolation model using nonlinear
                        least squares
fit_gp_scb_curve        Fit a monotone Gaussian process
                        sample-complexity curve
gendata                 Simulate data with appropriate structure to be
                        used in estimating sample complexity bounds
getpac                  Recalculate achieved sample complexity bounds
                        given different parameter inputs
interpolate_scb         Conduct interpolation on a list of data
interpolate_scb_gp      Interpolate sample-complexity curves using
                        monotone Gaussian processes
loss                    Utility function to define the least-squares
                        loss function to be optimized for 'simvcd()'
plot.empirical_scb_gp   Plot a monotone Gaussian process
                        sample-complexity fit
plot.empirical_scb_list
                        Plot method for an 'empirical_scb_list' object
plot.scb_data           Plot method for simulated sample complexity
                        bounds ('scb_data' object)
risk_bounds             Utility function to generate data points for
                        estimation of the VC Dimension of a
                        user-specified binary classification algorithm
                        given a specified sample size.
scb                     Calculate sample complexity bounds for a
                        classifier given target accuracy
simvcd                  Estimate the Vapnik-Chervonenkis (VC) dimension
                        of an arbitrary binary classification
                        algorithm.
summary.empirical_scb_gp
                        Summarize a monotone Gaussian process
                        sample-complexity fit
summary.empirical_scb_list
                        Summary of empirical sample complexity bound
                        results
