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Diagnosing Suboptimal Cotangent Disintegrations in Hamiltonian Monte Carlo
Michael Betancourt
When properly tuned, Hamiltonian Monte Carlo scales to some of the most challenging high-dimensional problems at the frontiers of applied statistics, but when that tuning is subopt…
Bayesian aggregation of average data: An application in drug development
Sebastian Weber, Andrew Gelman, Daniel Lee +3
Throughout the different phases of a drug development program, randomized trials are used to establish the tolerability, safety, and efficacy of a candidate drug. At each stage one…
Identifying the Optimal Integration Time in Hamiltonian Monte Carlo
Michael Betancourt
By leveraging the natural geometry of a smooth probabilistic system, Hamiltonian Monte Carlo yields computationally efficient Markov Chain Monte Carlo estimation. At least provided…
On the Geometric Ergodicity of Hamiltonian Monte Carlo
Samuel Livingstone, Michael Betancourt, Simon Byrne +1
We establish general conditions under which Markov chains produced by the Hamiltonian Monte Carlo method will and will not be geometrically ergodic. We consider implementations wit…