I2 Tieto- ja viestintätekniset sovellukset
AdaptiveParticleMCMC.jl (2020)
Vihola, M. (2020). AdaptiveParticleMCMC.jl. GitHub. https://github.com/mvihola/AdaptiveParticleMCMC.jl
JYU-tekijät tai -toimittajat
Julkaisun tiedot
Julkaisun kaikki tekijät tai toimittajat: Vihola, Matti
Julkaisuvuosi: 2020
Ilmestymispäivä: 28.06.2021
Kustantaja: GitHub
Julkaisun kieli: englanti
Pysyvä verkko-osoite: https://github.com/mvihola/AdaptiveParticleMCMC.jl
Julkaisun avoin saatavuus: Avoimesti saatavilla
Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava
Tiivistelmä
Simple implementation of adaptive proposals within particle Markov chain Monte Carlo (Andrieu, Doucet and Holenstein, 2010), based on the AdaptiveMCMC.jl and SequentialMonteCarlo.jl packages.
The package implemnents the following combinations:
Particle marginal Metropolis-Hastings with Adaptive Metropolis covariance adaptation (Haario, Saksman and Tamminen, 2001, and Andrieu and Moulines, 2006)
Particle Gibbs with Robust adaptive Metropolis acceptance rate based shape adaptation (Vihola, 2012) and Adaptive scaling within Adaptive Metropolis (e.g. Andrieu and Thoms, 2008)
These choices are discussed in
M. Vihola. Ergonomic and reliable Bayesian inference with adaptive Markov chain Monte Carlo. In W. W. Piegrorsch, R. Levine, H. H. Zhang, and T. C. M. Lee, editors, Handbook of Computational Statistics and Data Science, Wiley, to appear.
If you use this package in your work, please cite the publication above.
The package implemnents the following combinations:
Particle marginal Metropolis-Hastings with Adaptive Metropolis covariance adaptation (Haario, Saksman and Tamminen, 2001, and Andrieu and Moulines, 2006)
Particle Gibbs with Robust adaptive Metropolis acceptance rate based shape adaptation (Vihola, 2012) and Adaptive scaling within Adaptive Metropolis (e.g. Andrieu and Thoms, 2008)
These choices are discussed in
M. Vihola. Ergonomic and reliable Bayesian inference with adaptive Markov chain Monte Carlo. In W. W. Piegrorsch, R. Levine, H. H. Zhang, and T. C. M. Lee, editors, Handbook of Computational Statistics and Data Science, Wiley, to appear.
If you use this package in your work, please cite the publication above.
YSO-asiasanat: otanta; stokastiset prosessit; Markovin ketjut; Monte Carlo -menetelmät; algoritmit
Liittyvät organisaatiot
OKM-raportointi: Kyllä
