ERE_step_cycle          Does one Gibbs Step on a cycle
GibbsSteps_kcycle       Gibbs sampling step of a matrix in the ERE
                        model
Model.Indep.p.lambda    Combination of Independent Models for p and
                        lambda
Model.additivelink.exponential.fitness
                        Fitness model for liabilities matrix
Model.fitness.conditionalmeandegree
                        Mean out-degree of a node with given fitness in
                        the fitness model
Model.fitness.genlambdaparprior
                        Prior distribution for eta and zeta in the
                        fitness model
Model.fitness.meandegree
                        Mean out-degree of a random node the fitness
                        model
Model.lambda.GammaPrior
                        Model with Gamma Prior on Lambda
Model.lambda.Gammaprior_mult
                        Model Using Multiple Independent Components
Model.lambda.constant   Model for a Constant lambda
Model.lambda.constant.nonsquare
                        Model for a Constant lambda and Non-Square
                        Matrices
Model.p.BetaPrior       Model for a Random One-dimensional p
Model.p.Betaprior_mult
                        Model Using Multiple Independent Components
Model.p.Fitness.Servedio
                        Multiplicative Fitness Model for Power Law
Model.p.constant        Model for a Constant p
Model.p.constant.nonsquare
                        Model for a constant p and Non-Square Matrices
calibrate_ER            Calibrate ER model to a given density
calibrate_ER.nonsquare
                        Calibrate ER model to a given density with a
                        nonsquare matrix
calibrate_FitnessEmp    Calibrate empirical fitness model to a given
                        density
choosethin              Calibrate Thinning
cloneMatrix             Creates a deep copy of a matrix
default                 Default of Banks
default_cascade         Default Cascade
default_clearing        Clearing Vector with Bankruptcy Costs
diagnose                Outputs Effective Sample Size Diagonistics for
                        MCMC run
findFeasibleMatrix      Finds a Nonnegative Matrix Satisfying Row and
                        Column Sums
findFeasibleMatrix_targetmean
                        Creates a feasible starting matrix with a
                        desired mean average degree
genL                    Generate Liabilities Matrix from Prior
getfeasibleMatr         Creates a feasible starting matrix
sample_ERE              Sample from the ERE model with given row and
                        column sums
sample_HierarchicalModel
                        Sample from Hierarchical Model with given Row
                        and Column Sums
steps_ERE               Perform Steps of the Gibbs Sampler of the ERE
                        model
