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 |
ERE_step_cycle |
Does one Gibbs Step on a cycle |
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 |
GibbsSteps_kcycle |
Gibbs sampling step of a matrix in the ERE model |
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.Indep.p.lambda |
Combination of Independent Models for p and lambda |
Model.lambda.constant |
Model for a Constant lambda |
Model.lambda.constant.nonsquare |
Model for a Constant lambda and Non-Square Matrices |
Model.lambda.GammaPrior |
Model with Gamma Prior on Lambda |
Model.lambda.Gammaprior_mult |
Model Using Multiple Independent Components |
Model.p.BetaPrior |
Model for a Random One-dimensional p |
Model.p.Betaprior_mult |
Model Using Multiple Independent Components |
Model.p.constant |
Model for a Constant p |
Model.p.constant.nonsquare |
Model for a constant p and Non-Square Matrices |
Model.p.Fitness.Servedio |
Multiplicative Fitness Model for Power Law |
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 |