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The Metropolis algorithm is a widely used procedure for sampling
from a specified distribution on a large finite set. We survey what is
rigorously known about running times. This includes work from ...
Eigen Analysis for Some Examples of the Metropolis Algorithm
Analysis the metropolis algorithm example
2015/7/14
Eigen Analysis for Some Examples of the Metropolis Algorithm.
What Do We Know about the Metropolis Algorithm.
Numerical Results for the Metropolis Algorithm。
Examples comparing Importance Sampling and the Metropolis algorithm
Sampling order markov chain monte carlo simulation technology the markov chain
2015/7/8
Importance sampling, particularly sequential and adaptive importance sampling, have emerged as competitive simulation techniques to Markov–chain Monte–Carlo techniques. We compare importance sampling ...
Micro-local Analysis for the Metropolis Algorithm
Convergence rate algorithm random eigenvalues and eigenvectors
2015/7/8
We prove sharp rates of convergence to stationarity for a simple case of the Metropolis algorithm: the placement of a single disc of radius h randomly into the
interval [−1 − h, 1 + h], w...
Geometric Analysis for the Metropolis Algorithm on Lipschitz Domains
Geometry comparison Steve Nash sobolev inequality the convergence rate
2015/7/7
This paper gives geometric tools: comparison, Nash and Sobolev inequalities for pieces of the relevent Markov operators, that give useful bounds on rates of convergence for the Metropolis algorithm. A...
Recently, the idea of classical Metropolis sampling through Markov chains has been generalized for quantum Hamiltonians. However, the underlying Markov chain of this algorithm is still classical in na...