메뉴 건너뛰기




Volumn 8, Issue 2, 2013, Pages 411-438

An adaptive sequential monte carlo sampler

Author keywords

Adaptive MCMC; Adaptive sequential monte carlo; Bayesian mixture analysis; Optimal scaling; Stochastic optimization

Indexed keywords


EID: 84878536475     PISSN: 19360975     EISSN: 19316690     Source Type: Journal    
DOI: 10.1214/13-BA814     Document Type: Article
Times cited : (52)

References (48)
  • 2
    • 57849088168 scopus 로고    scopus 로고
    • A tutorial on adaptive MCMC
    • Andrieu, C. and Thoms, J. (2008). "A tutorial on adaptive MCMC." Statistics and Computing, 18(4): 343-373.
    • (2008) Statistics and Computing , vol.18 , Issue.4 , pp. 343-373
    • Andrieu, C.1    Thoms, J.2
  • 3
    • 33747062507 scopus 로고    scopus 로고
    • On adaptive Markov chain Monte Carlo algorithms
    • Atchadé, Y. and Rosenthal, J. (2005). "On adaptive Markov chain Monte Carlo algorithms." Bernoulli, 11(5): 815-828.
    • (2005) Bernoulli , vol.11 , Issue.5 , pp. 815-828
    • Atchadé, Y.1    Rosenthal, J.2
  • 6
    • 2242491935 scopus 로고    scopus 로고
    • Computational and Inferential Difficulties with Mixture Posterior Distributions
    • Celeux, G., Hurn, M., and Robert, C. P. (2000). "Computational and Inferential Difficulties with Mixture Posterior Distributions." Journal of the American Statistical Association, 95(451): 957-970.
    • (2000) Journal of the American Statistical Association , vol.95 , Issue.451 , pp. 957-970
    • Celeux, G.1    Hurn, M.2    Robert, C.P.3
  • 7
    • 0012338718 scopus 로고    scopus 로고
    • A sequential particle filter method for static models
    • Chopin, N. (2002). "A sequential particle filter method for static models." Biometrika, 89(3): 539-552.
    • (2002) Biometrika , vol.89 , Issue.3 , pp. 539-552
    • Chopin, N.1
  • 8
    • 57849133035 scopus 로고    scopus 로고
    • Adaptive methods for sequential importance sampling with application to state space models
    • Cornebise, J., Moulines, E., and Olsson, J. (2008). "Adaptive methods for sequential importance sampling with application to state space models." Statistics and Com-puting, 18(4): 461-480.
    • (2008) Statistics and Com-puting , vol.18 , Issue.4 , pp. 461-480
    • Cornebise, J.1    Moulines, E.2    Olsson, J.3
  • 17
    • 41549102613 scopus 로고    scopus 로고
    • Computational Methods for Complex Stochastic Systems: A Review of Some Alternatives to MCMC
    • Fearnhead, P. (2008). "Computational Methods for Complex Stochastic Systems: A Review of Some Alternatives to MCMC." Statistics and Computing, 18: 151-171.
    • (2008) Statistics and Computing , vol.18 , pp. 151-171
    • Fearnhead, P.1
  • 18
    • 33847369235 scopus 로고    scopus 로고
    • Springer. Gamerman, D. and Lopes, H. F. (2006). Markov Chain Monte Carlo: Stochastic Sim-ulation for Bayesian Inference (2nd ed.). Chpman & Hall/CRC
    • Frühwirth-Schnatter, S. (2006). Finite Mixture and Markov Switching Models. Springer. Gamerman, D. and Lopes, H. F. (2006). Markov Chain Monte Carlo: Stochastic Sim-ulation for Bayesian Inference (2nd ed.). Chpman & Hall/CRC.
    • (2006) Finite Mixture and Markov Switching Models
    • Frühwirth-Schnatter, S.1
  • 19
    • 0012224228 scopus 로고    scopus 로고
    • Asymptotic Normality of Posterior Distributions in High Dimensional Linear Models
    • Ghosal, S. (1999). "Asymptotic Normality of Posterior Distributions in High Dimensional Linear Models." Bernoulli, 5(2): 315-331.
    • (1999) Bernoulli , vol.5 , Issue.2 , pp. 315-331
    • Ghosal, S.1
  • 20
    • 0035648076 scopus 로고    scopus 로고
    • Following a moving target - Monte Carlo inference for dynamic Bayesian models, Journal of the Royal Statistical Society
    • Gilks, W. and Berzuini, C. (1999). "Following a moving target - Monte Carlo inference for dynamic Bayesian models." Journal of the Royal Statistical Society, Series B, 63(1): 127-146.
    • (1999) Series B , vol.63 , Issue.1 , pp. 127-146
    • Gilks, W.1    Berzuini, C.2
  • 24
    • 0038563932 scopus 로고    scopus 로고
    • An Adaptive Metropolis algorithm
    • Haario, H., Saksman, E., and Tamminen, J. (1998). "An Adaptive Metropolis algorithm." Bernoulli, 7: 223-242.
    • (1998) Bernoulli , vol.7 , pp. 223-242
    • Haario, H.1    Saksman, E.2    Tamminen, J.3
  • 25
    • 77956890234 scopus 로고
    • Monte Carlo sampling methods using Markov chains and their applications
    • Hastings, W. K. (1970). "Monte Carlo sampling methods using Markov chains and their applications." Biometrika, 57(1): 97-109.
    • (1970) Biometrika , vol.57 , Issue.1 , pp. 97-109
    • Hastings, W.K.1
  • 26
  • 28
    • 34547863202 scopus 로고    scopus 로고
    • On population-based simulation for static inference
    • Jasra, A., Stephens, D. A., and Holmes, C. C. (2007). "On population-based simulation for static inference." Statistics and Computing, 17(3): 263-279.
    • (2007) Statistics and Computing , vol.17 , Issue.3 , pp. 263-279
    • Jasra, A.1    Stephens, D.A.2    Holmes, C.C.3
  • 29
    • 21844487298 scopus 로고
    • Theoretical and Empirical Properties of the Genetic Algorithm as a Numerical Optimizer
    • Jennison, C. and Sheehan, N. (1995). "Theoretical and Empirical Properties of the Genetic Algorithm as a Numerical Optimizer." Journal of Computational and Graphical Statistics, 4(4): 296-318
    • (1995) Journal of Computational and Graphical Statistics , vol.4 , Issue.4 , pp. 296-318
    • Jennison, C.1    Sheehan, N.2
  • 30
    • 0030304310 scopus 로고    scopus 로고
    • Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models
    • Kitagawa, G. (1996). "Monte Carlo Filter and Smoother for Non-Gaussian Nonlinear State Space Models." Journal of Computational and Graphical Statistics, 5(1): 1-25.
    • (1996) Journal of Computational and Graphical Statistics , vol.5 , Issue.1 , pp. 1-25
    • Kitagawa, G.1
  • 32
    • 0003665481 scopus 로고    scopus 로고
    • chapter 10 Combined Parameter and State Estimation in Simulation-Based Filtering. Springer- Verlag New York
    • Liu, J. and West, M. (2001). Sequential Monte Carlo Methods in Practice, chapter 10: Combined Parameter and State Estimation in Simulation-Based Filtering. Springer- Verlag New York.
    • (2001) Sequential Monte Carlo Methods in Practice
    • Liu, J.1    West, M.2
  • 34
    • 0032359151 scopus 로고    scopus 로고
    • Sequential Monte Carlo Methods for Dynamic Systems
    • Liu, J. S. (1998). "Sequential Monte Carlo Methods for Dynamic Systems." Journal of the American Statistical Association, 93(443): 1032-1044.
    • (1998) Journal of the American Statistical Association , vol.93 , Issue.443 , pp. 1032-1044
    • Liu, J.S.1
  • 37
    • 0000273048 scopus 로고    scopus 로고
    • Annealed Importance Sampling
    • Neal, R. (2001). "Annealed Importance Sampling." Statistics and Computing, 11(2): 125-139.
    • (2001) Statistics and Computing , vol.11 , Issue.2 , pp. 125-139
    • Neal, R.1
  • 38
    • 77949374261 scopus 로고    scopus 로고
    • Adaptively scaling the Metropolis algorithm using expected squared jumped distance
    • Pasarica, C. and Gelman, A. (2010). "Adaptively scaling the Metropolis algorithm using expected squared jumped distance." Statistica Sinica, 20: 343-364.
    • (2010) Statistica Sinica , vol.20 , pp. 343-364
    • Pasarica, C.1    Gelman, A.2
  • 39
    • 0013037129 scopus 로고    scopus 로고
    • Optimal Scaling for Various Metropolis-Hastings Algorithms
    • Roberts, G. and Rosenthal, J. (2001). "Optimal Scaling for Various Metropolis-Hastings Algorithms." Statistical Science, 16(4): 351-367.
    • (2001) Statistical Science , vol.16 , Issue.4 , pp. 351-367
    • Roberts, G.1    Rosenthal, J.2
  • 41
    • 85132364916 scopus 로고    scopus 로고
    • Exponential Convergence of Langevin Distributions and Their Discrete Approximations
    • Roberts, G. O. and Tweedie, R. L. (1996). "Exponential Convergence of Langevin Distributions and Their Discrete Approximations." Bernoulli, 2(4): 341-363.
    • (1996) Bernoulli , vol.2 , Issue.4 , pp. 341-363
    • Roberts, G.O.1    Tweedie, R.L.2
  • 42
    • 84872617354 scopus 로고    scopus 로고
    • Sequential Monte Carlo on large binary sampling spaces
    • Schäfer, C. and Chopin, N. (2013). "Sequential Monte Carlo on large binary sampling spaces." Statistics and Computing, 23: 163-184.
    • (2013) Statistics and Computing , vol.23 , pp. 163-184
    • Schäfer, C.1    Chopin, N.2
  • 43
    • 72249090639 scopus 로고    scopus 로고
    • Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets
    • Sherlock, C. and Roberts, G. (2009). "Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets." Bernoulli, 15(3): 774-798.
    • (2009) Bernoulli , vol.15 , Issue.3 , pp. 774-798
    • Sherlock, C.1    Roberts, G.2
  • 44
    • 0034354410 scopus 로고    scopus 로고
    • Dealing with label switching in mixture models, Journal of the Royal Statistical Society
    • Stephens, M. (2000). "Dealing with label switching in mixture models." Journal of the Royal Statistical Society, Series B, 62(4): 795-809
    • (2000) Series B , vol.62 , Issue.4 , pp. 795-809
    • Stephens, M.1
  • 45
    • 0036475891 scopus 로고    scopus 로고
    • Particle filters for state-space models with the presence of unknown static parameters
    • Storvik, G. (2002). "Particle filters for state-space models with the presence of unknown static parameters." IEEE Transactions on Signal Processing, 50: 281-289.
    • (2002) IEEE Transactions on Signal Processing , vol.50 , pp. 281-289
    • Storvik, G.1
  • 46
    • 33745603720 scopus 로고    scopus 로고
    • A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces
    • Ter Braak, C. J. F. (2006). "A Markov Chain Monte Carlo version of the genetic algorithm Differential Evolution: easy Bayesian computing for real parameter spaces." Statistics and Computing, 16(3): 239-249.
    • (2006) Statistics and Computing , vol.16 , Issue.3 , pp. 239-249
    • Ter Braak, C.J.F.1
  • 47
    • 0000417862 scopus 로고
    • Mixture models, Monte Carlo Bayesian updating and dynamic models
    • West, M. (1993). "Mixture models, Monte Carlo, Bayesian updating and dynamic models." Computing Science and Statistics, 24: 325-333.
    • (1993) Computing Science and Statistics , vol.24 , pp. 325-333
    • West, M.1
  • 48
    • 0002338687 scopus 로고
    • A genetic algorithm tutorial
    • Whitley, D. (1994). "A genetic algorithm tutorial." Statistics and Computing, 4: 65-85.
    • (1994) Statistics and Computing , vol.4 , pp. 65-85
    • Whitley, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.