CalcHorseBin            Creates the the working response for all
                        responses for glmnet binomial family
CalcHorseEBin           Creates the probabilities and working response
                        for the glmnet update for a given response with
                        a binomial family
SetEq                   SetEq test set equivalence of two clustering
                        sets
beta_adjust             Adjusts the value of the coefficients to
                        account for the scaling of x and y.
beta_adjust_bin         Adjusts the value of the binomial coefficients
                        to account for the scaling of x.
bin_horse               The workhorse function for the binomial updates
                        in mcen.  It uses IRWLS glmnet updates to solve
                        the regression problem.
cluster                 Wrapper function for different clustering
                        methods
cluster.vals            Returns the cluster values from a cv.mcen
                        object.
coef.cv.mcen            Returns the coefficients from the cv.mcen
                        object with the smallest cross-validation
                        error.
coef.mcen               Returns the coefficients from an mcen object.
cv.mcen                 Cross validation for mcen function
get_best_cvm            Gets the index position for the model with the
                        smallest cross-validation error.
matrix_multiply         matrix multiply
mcen                    Fits an MCEN model
mcen.init               Provides initial estimates for the mcen
                        functionF
mcen_bin_workhorse      Calculates cluster assignment and coefficient
                        estimates for a binomial mcen.
mcen_workhorse          Estimates the clusters and provides the
                        coefficients for an mcen object
pred_eval               Calculates the out of sample likelihood for an
                        mcen object
pred_eval.mbinom_mcen   Evaluates prediction error for multiple
                        binomial responses.
pred_eval.mgauss_mcen   Calculates the prediction error for a
                        mgauss_mcen object.
predict.cv.mcen         Makes predictions from the model with the
                        smallest cross-validation error.
predict.mcen            predictions from a mcen model
print.cv.mcen           Prints nice output for a cv.mcen object.
print.mcen              Prints nice output for an mcen object.
randomly_assign         randomly assign n samples to k groups
squared_error           Calculates sum of squared error between two
                        vectors or matrices
vl_binom                Calculates out of sample error on the binomial
                        likelihood
