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A new strategy for speeding Markov chain Monte Carlo algorithms
Antonietta Mira, Daniel J. Sargent
Quantitative Health Sciences
Research output
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Contribution to journal
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Article
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peer-review
7
Scopus citations
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Dive into the research topics of 'A new strategy for speeding Markov chain Monte Carlo algorithms'. Together they form a unique fingerprint.
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Mathematics
Markov Chain Monte Carlo Algorithms
99%
Chain
62%
Strategy
58%
kernel
42%
Stationary Distribution
41%
Rao-Blackwellization
34%
Metropolis-Hastings
27%
Metropolis-Hastings Algorithm
27%
Long-run
24%
Gibbs Sampling
24%
Gibbs Sampler
24%
Tuning
24%
Markov Chain Monte Carlo Methods
23%
Updating
22%
Statistical Model
20%
Drawing
20%
History
18%
Entire
17%
State Space
17%
Interval
12%
Framework
11%
Estimate
9%
Business & Economics
Markov Chain Monte Carlo
99%
Stationary Distribution
70%
Metropolis-Hastings Algorithm
46%
Gibbs Sampler
41%
Gibbs Sampling
40%
Statistical Model
38%
Markov Chain Monte Carlo Methods
36%
State Space
30%
Inference
22%