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Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition
Open accessAbstract
While there have been few theoretical contributions on the Markov Chain Monte Carlo (MCMC) methods in the past decade, current understanding and application of MCMC to the solution of inference problems has increased by leaps and bounds. Incorporating changes in theory and highlighting new applications, Markov Chain Monte Carlo: Stochastic Simul
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“In our analysis, we have shown that CBT, but not BT, may have a positive association with various domains of a patient’s life, such as mental functioning, social and study-related relationships, level of discomfort, and engagement in everyday activities.”
From Different Types and Acceptability of Psychotherapies for Acute Anxiety Disorders in Children and Adolescents: A Network Meta-analysis (2019) · cites this paper as [44]
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Metadata
- Authors
- Gamerman, D., & Lopes, H. F.
- ORCID
- Lopes, Hedibert F.
- Venue
- Chapman & Hall/CRC eBooks
- Publisher
- Chapman and Hall/CRC
- Published
- 2006-05-10
- OpenAlex
- W4256038730
- Cited by
- 1,097
- References
- 0
- Citations by year
- 2026: 31 · 2025: 71 · 2024: 72 · 2023: 51 · 2022: 82 · 2021: 75 · 2020: 90 · 2019: 81 · 2018: 56 · 2017: 54 · 2016: 62 · 2015: 55 · 2014: 53 · 2013: 54 · 2012: 62
- FWCI
- 4.94
- Type
- book
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Chapman & Hall/CRC eBooks (publishedVersion)
- Topics
- Physical Sciences › Mathematics › Statistics and Probability › Markov Chains and Monte Carlo Methods
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
- Physical Sciences › Physics and Astronomy › Condensed Matter Physics › Theoretical and Computational Physics
- Keywords
- Markov chain Monte Carlo, stochastic simulation, Bayesian inference, Markov chains, sampling methods, statistical inference
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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