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xsample(): An R function for sampling linear inverse problems

Publication Date
  • Algorithms
  • Linear
  • Modelling
  • Computer Science


An R function is implemented that uses Markov chain Monte Carlo (MCMC) algorithms to uniformly sample the feasible region of constrained linear problems. Two existing hit-and-run sampling algorithms are implemented, together with a new algorithm where an MCMC step reflects on the inequality constraints. The new algorithm is more robust compared to the hit-and-run methods, at a small cost of increased calculation time.

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