mcunit - Unit Tests for MC Methods

Unit testing for Monte Carlo methods, particularly Markov Chain Monte Carlo (MCMC) methods, are implemented as extensions of the 'testthat' package. The MCMC methods check whether the MCMC chain has the correct invariant distribution. They do not check other properties of successful samplers such as whether the chain can reach all points, i.e. whether is recurrent. The tests require the ability to sample from the prior and to run steps of the MCMC chain. The methodology is described in Gandy and Scott (2020) <arXiv:2001.06465>.

Last updated 3 years ago

4.00 score 1 scripts 184 downloads

systemicrisk - Systemic Risk and Network Reconstruction

Analysis of risk through liability matrices. Contains a Gibbs sampler for network reconstruction, where only row and column sums of the liabilities matrix as well as some other fixed entries are observed, following the methodology of Gandy&Veraart (2016) <doi:10.1287/mnsc.2016.2546>. It also incorporates models that use a power law distribution on the degree distribution.

Last updated 10 months ago

cpp

3.88 score 5 stars 51 scripts 539 downloads

simctest - Safe Implementation of Monte Carlo Tests

Algorithms for the implementation and evaluation of Monte Carlo tests, as well as for their use in multiple testing procedures.

Last updated 4 months ago

3.85 score 2 dependents 39 scripts 606 downloads

spcadjust - Functions for Calibrating Control Charts

Calibration of thresholds of control charts such as CUSUM charts based on past data, taking estimation error into account.

Last updated 8 years ago

3.35 score 1 stars 37 scripts 190 downloads

chopthin - The Chopthin Resampler

Resampling is a standard step in particle filtering and in sequential Monte Carlo. This package implements the chopthin resampler, which keeps a bound on the ratio between the largest and the smallest weights after resampling.

Last updated 7 years ago

cpp

1.00 score 3 scripts 558 downloads