A toolbox for systemic risk based on liabilities matrices. Contains a Gibbs sampler for liabilities matrices where only row and column sums of the liabilities matrix as well as some other fixed entries are observed. Includes models for power law distribution on the degree distribution.

Author | Axel Gandy and Luitgard A.M. Veraart |

Date of publication | 2017-01-08 13:37:33 |

Maintainer | Axel Gandy <a.gandy@imperial.ac.uk> |

License | GPL-3 |

Version | 0.4 |

**calibrate_ER:** Calibrate ER model to a given density

**calibrate_FitnessEmp:** Calibrate empirical fitness model to a given density

**choosethin:** Calibrate Thinning

**cloneMatrix:** Crates 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 Diagonis 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...

**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.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.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.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

systemicrisk

systemicrisk/inst

systemicrisk/inst/CITATION

systemicrisk/inst/NEWS.Rd

systemicrisk/inst/doc

systemicrisk/inst/doc/Introduction.Rmd

systemicrisk/inst/doc/Introduction.R

systemicrisk/inst/doc/HierarchicalModels.R

systemicrisk/inst/doc/HierarchicalModels.Rmd

systemicrisk/inst/doc/Introduction.html

systemicrisk/inst/doc/HierarchicalModels.html

systemicrisk/tests

systemicrisk/tests/testthat.R

systemicrisk/tests/testthat

systemicrisk/tests/testthat/test_HierarchicalModels_choosethin.R

systemicrisk/tests/testthat/test_HierarchicalModels.R

systemicrisk/tests/testthat/test-gibbs_kcycle.R

systemicrisk/tests/testthat/test_FeasibleMatrix.R

systemicrisk/src

systemicrisk/src/lib_FeasibleMatrix.cpp

systemicrisk/src/lib_sample_kcycle.cpp

systemicrisk/src/RcppExports.cpp

systemicrisk/NAMESPACE

systemicrisk/R

systemicrisk/R/ExponentialFitnessLinkFun.R
systemicrisk/R/lib_Network_Evaluations.R
systemicrisk/R/lib_FindFeasibleMatrix.R
systemicrisk/R/AdjustableModels.R
systemicrisk/R/HierarchicalModels.R
systemicrisk/R/lib_ErdosRenyExponential_MCMC.R
systemicrisk/R/RcppExports.R
systemicrisk/vignettes

systemicrisk/vignettes/Introduction.Rmd

systemicrisk/vignettes/HierarchicalModels.Rmd

systemicrisk/MD5

systemicrisk/build

systemicrisk/build/vignette.rds

systemicrisk/DESCRIPTION

systemicrisk/man

systemicrisk/man/sample_HierarchicalModel.Rd
systemicrisk/man/calibrate_FitnessEmp.Rd
systemicrisk/man/default_clearing.Rd
systemicrisk/man/Model.fitness.meandegree.Rd
systemicrisk/man/findFeasibleMatrix_targetmean.Rd
systemicrisk/man/Model.p.Fitness.Servedio.Rd
systemicrisk/man/diagnose.Rd
systemicrisk/man/Model.lambda.Gammaprior_mult.Rd
systemicrisk/man/default_cascade.Rd
systemicrisk/man/sample_ERE.Rd
systemicrisk/man/Model.p.Betaprior_mult.Rd
systemicrisk/man/Model.lambda.GammaPrior.Rd
systemicrisk/man/Model.p.BetaPrior.Rd
systemicrisk/man/findFeasibleMatrix.Rd
systemicrisk/man/default.Rd
systemicrisk/man/choosethin.Rd
systemicrisk/man/Model.additivelink.exponential.fitness.Rd
systemicrisk/man/Model.fitness.genlambdaparprior.Rd
systemicrisk/man/steps_ERE.Rd
systemicrisk/man/genL.Rd
systemicrisk/man/Model.Indep.p.lambda.Rd
systemicrisk/man/cloneMatrix.Rd
systemicrisk/man/Model.lambda.constant.Rd
systemicrisk/man/ERE_step_cycle.Rd
systemicrisk/man/calibrate_ER.Rd
systemicrisk/man/Model.p.constant.Rd
systemicrisk/man/GibbsSteps_kcycle.Rd
systemicrisk/man/getfeasibleMatr.Rd
systemicrisk/man/Model.fitness.conditionalmeandegree.Rd
Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.