Interface | Description |
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MetropolisHastings.ProposalDensityFunction |
Defines the density of a proposal function, i.e.
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Class | Description |
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AbstractMetropolis |
The Metropolis algorithm is a Markov Chain Monte Carlo algorithm, which requires only a function
f proportional to the PDF from which we wish to sample.
|
Metropolis |
This basic Metropolis implementation assumes using symmetric proposal function.
|
MetropolisHastings |
A generalization of the Metropolis algorithm, which allows asymmetric proposal
functions.
|
MetropolisUtils |
Utility functions for Metropolis algorithms.
|
RobustAdaptiveMetropolis |
A variation of Metropolis, that uses the estimated covariance of the target
distribution in the proposal distribution, based on a paper by Vihola (2011).
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