Man pages for systemicrisk
A Toolbox for Systemic Risk

calibrate_ERCalibrate ER model to a given density
calibrate_FitnessEmpCalibrate empirical fitness model to a given density
choosethinCalibrate Thinning
cloneMatrixCrates a deep copy of a matrix
defaultDefault of Banks
default_cascadeDefault Cascade
default_clearingClearing Vector with Bankruptcy Costs
diagnoseOutputs Effective Sample Size Diagonis for MCMC run
ERE_step_cycleDoes one Gibbs Step on a cycle
findFeasibleMatrixFinds a Nonnegative Matrix Satisfying Row and Column Sums
findFeasibleMatrix_targetmeanCreates a feasible starting matrix with a desired mean...
genLGenerate Liabilities Matrix from Prior
getfeasibleMatrCreates a feasible starting matrix
GibbsSteps_kcycleGibbs sampling step of a matrix in the ERE model
Model.additivelink.exponential.fitnessFitness model for liabilities matrix
Model.fitness.conditionalmeandegreeMean out-degree of a node with given fitness in the fitness...
Model.fitness.genlambdaparpriorPrior distribution for eta and zeta in the fitness model
Model.fitness.meandegreeMean out-degree of a random node the fitness model
Model.Indep.p.lambdaCombination of Independent Models for p and lambda
Model.lambda.constantModel for a Constant lambda
Model.lambda.GammaPriorModel with Gamma Prior on Lambda
Model.lambda.Gammaprior_multModel Using Multiple Independent Components
Model.p.BetaPriorModel for a Random One-dimensional p
Model.p.Betaprior_multModel Using Multiple Independent Components
Model.p.constantModel for a Constant p
Model.p.Fitness.ServedioMultiplicative Fitness Model for Power Law
sample_ERESample from the ERE model with given row and column sums
sample_HierarchicalModelSample from Hierarchical Model with given Row and Column Sums
steps_EREPerform Steps of the Gibbs Sampler of the ERE model
systemicrisk documentation built on May 30, 2017, 1:47 a.m.