메뉴 건너뛰기




Volumn 23, Issue , 2012, Pages 539-555

Nonasymptotic Bounds on the Mean Square Error for MCMC Estimates via Renewal Techniques

Author keywords

[No Author keywords available]

Indexed keywords

CHAINS; MONTE CARLO METHODS;

EID: 84888322375     PISSN: 21941009     EISSN: 21941017     Source Type: Conference Proceeding    
DOI: 10.1007/978-3-642-27440-4_31     Document Type: Conference Paper
Times cited : (5)

References (35)
  • 1
    • 33947279458 scopus 로고    scopus 로고
    • On the geometric ergodicity of Metropolis-Hastings algorithms
    • Y.F. Atchade, F. Perron (2007): On the geometric ergodicity of Metropolis-Hastings algorithms. Statistics 41, 77-84.
    • (2007) Statistics , vol.41 , pp. 77-84
    • Atchade, Y.F.1    Perron, F.2
  • 2
    • 0000991156 scopus 로고
    • A new approach to the limit theory of recurrent Markov chains
    • K.B. Athreya and P. Ney (1978): A new approach to the limit theory of recurrent Markov chains, Trans. Amer. Math. Soc. 245, 493-501.
    • (1978) Trans. Amer. Math. Soc , vol.245 , pp. 493-501
    • Athreya, K.B.1    Ney, P.2
  • 3
    • 14544277112 scopus 로고    scopus 로고
    • Renewal Theory and Computable Convergence Rates for Geometrically Ergodic Markov Chains
    • P.H. Baxendale (2005): Renewal Theory and Computable Convergence Rates for Geometrically Ergodic Markov Chains. Ann. Appl. Prob. 15, 700-738.
    • (2005) Ann. Appl. Prob , vol.15 , pp. 700-738
    • Baxendale, P.H.1
  • 4
    • 39049143299 scopus 로고    scopus 로고
    • A Regeneration Proof of the Central Limit Theorem for Uniformly Ergodic Markov Chains
    • W. Bednorz, R. Latała and K. Łatuszyński (2008): A Regeneration Proof of the Central Limit Theorem for Uniformly Ergodic Markov Chains. Elect. Comm. in Probab. 13, 85-98.
    • (2008) Elect. Comm. in Probab , vol.13 , pp. 85-98
    • Bednorz, W.1    Latała, R.2    Łatuszyński, K.3
  • 7
    • 0000580574 scopus 로고    scopus 로고
    • V-subgeometric ergodicity for a Hastings-Metropolis algorithm
    • G. Fort and E. Moulines (2000): V-subgeometric ergodicity for a Hastings-Metropolis algorithm. Statist. Probab. Lett. 49, 401-410.
    • (2000) Statist. Probab. Lett , vol.49 , pp. 401-410
    • Fort, G.1    Moulines, E.2
  • 10
    • 0037079674 scopus 로고    scopus 로고
    • Hoeffding's inequality for uniformly ergodic Markov chains
    • P.W. Glynn and D. Ormoneit (2002): Hoeffding's inequality for uniformly ergodic Markov chains, Statist. Probab. Lett. 56, 143-146.
    • (2002) Statist. Probab. Lett , vol.56 , pp. 143-146
    • Glynn, P.W.1    Ormoneit, D.2
  • 11
  • 12
    • 0038569359 scopus 로고    scopus 로고
    • Geometric ergodicity of Gibbs and block Gibbs samplers for Hierarchical Random Effects Model
    • J.P. Hobert and C.J. Geyer (1998): Geometric ergodicity of Gibbs and block Gibbs samplers for Hierarchical Random Effects Model. J. Multivariate Anal. 67, 414-439.
    • (1998) J. Multivariate Anal , vol.67 , pp. 414-439
    • Hobert, J.P.1    Geyer, C.J.2
  • 13
    • 2142780945 scopus 로고    scopus 로고
    • On the Applicability of Regenerative Simulation in Markov Chain Monte Carlo
    • J.P. Hobert, G.L. Jones, B. Presnell, and J.S. Rosenthal (2002): On the Applicability of Regenerative Simulation in Markov Chain Monte Carlo. Biometrika 89, 731-743.
    • (2002) Biometrika , vol.89 , pp. 731-743
    • Hobert, J.P.1    Jones, G.L.2    Presnell, B.3    Rosenthal, J.S.4
  • 14
    • 9744242175 scopus 로고    scopus 로고
    • A mixture representation of with applications in Markov chain Monte Carlo and perfect sampling
    • J.P. Hobert and C.P. Robert (2004): A mixture representation of with applications in Markov chain Monte Carlo and perfect sampling. Ann. Appl. Probab. 14 1295-1305.
    • (2004) Ann. Appl. Probab , vol.14 , pp. 1295-1305
    • Hobert, J.P.1    Robert, C.P.2
  • 15
    • 38249043088 scopus 로고
    • Random generation of combinatorial structures fro, a uniform distribution
    • M.R. Jerrum, L.G. Valiant, V.V. Vazirani (1986): Random generation of combinatorial structures fro, a uniform distribution. Theoretical Computer Science 43, 169-188.
    • (1986) Theoretical Computer Science , vol.43 , pp. 169-188
    • Jerrum, M.R.1    Valiant, L.G.2    Vazirani, V.V.3
  • 16
    • 24344493048 scopus 로고    scopus 로고
    • Sufficient burn-in for Gibbs samplers for a hierarchical random effects model
    • G.L. Jones, J.P. Hobert (2004): Sufficient burn-in for Gibbs samplers for a hierarchical random effects model. Ann. Statist. 32, pp. 784-817.
    • (2004) Ann. Statist , vol.32 , pp. 784-817
    • Jones, G.L.1    Hobert, J.P.2
  • 17
    • 78649758959 scopus 로고    scopus 로고
    • Gibbs sampling for a Bayesian hierarchical general linear model
    • A.A. Johnson and G.L. Jones (2010): Gibbs sampling for a Bayesian hierarchical general linear model. Electronic J. Statist. 4, 313-333.
    • (2010) Electronic J. Statist , vol.4 , pp. 313-333
    • Johnson, A.A.1    Jones, G.L.2
  • 20
    • 78649724375 scopus 로고    scopus 로고
    • Rigorous confidence bounds forMCMC under a geometric drift condition
    • K. Łatuszyński, W. Niemiro (2011): Rigorous confidence bounds forMCMC under a geometric drift condition. J. of Complexity 27, 23-38.
    • (2011) J. of Complexity , vol.27 , pp. 23-38
    • Łatuszyński, K.1    Niemiro, W.2
  • 21
    • 0009061218 scopus 로고
    • On excess over the boundary
    • G. Lorden: On excess over the boundary. Ann. Math. Statist. 41, 520-527, 1970.
    • (1970) Ann. Math. Statist , vol.41 , pp. 520-527
    • Lorden, G.1
  • 22
    • 0030551974 scopus 로고    scopus 로고
    • Rates of convergence of the Hastings and Metropolis algorithms
    • K.L. Mengersen, L.R. Tweedie (1996): Rates of convergence of the Hastings and Metropolis algorithms. Ann. Statist. 24, 1, 101-121.
    • (1996) Ann. Statist , vol.24 , Issue.1 , pp. 101-121
    • Mengersen, K.L.1    Tweedie, L.R.2
  • 24
  • 26
    • 67949089777 scopus 로고    scopus 로고
    • Fixed precision MCMC Estimation by Median of Products of Averages
    • W. Niemiro, P. Pokarowski (2009): Fixed precision MCMC Estimation by Median of Products of Averages. J. Appl. Probab. 46 (2), 309-329.
    • (2009) J. Appl. Probab , vol.46 , Issue.2 , pp. 309-329
    • Niemiro, W.1    Pokarowski, P.2
  • 27
    • 0000427555 scopus 로고
    • A splitting technique for Harris recurrent Markov chains
    • E. Nummelin (1978): A splitting technique for Harris recurrent Markov chains, Z. Wahr. Verw. Geb. 43, 309-318.
    • (1978) Z. Wahr. Verw. Geb , vol.43 , pp. 309-318
    • Nummelin, E.1
  • 30
    • 0002074149 scopus 로고    scopus 로고
    • Geometric ergodicity and hybridMarkov chains
    • G.O. Roberts and J.S. Rosenthal (1997): Geometric ergodicity and hybridMarkov chains. Elec. Comm. Prob. 2 (2).
    • (1997) Elec. Comm. Prob , vol.2 , Issue.2
    • Roberts, G.O.1    Rosenthal, J.S.2
  • 31
    • 84890736685 scopus 로고    scopus 로고
    • General state space Markov chains and MCMC algorithms
    • G.O. Roberts and J.S. Rosenthal (2004): General state space Markov chains and MCMC algorithms. Probability Surveys 1, 20-71.
    • (2004) Probability Surveys , vol.1 , pp. 20-71
    • Roberts, G.O.1    Rosenthal, J.S.2
  • 32
    • 84923618271 scopus 로고
    • Minorization conditions and convergence rates for Markov chains
    • J.S. Rosenthal (1995): Minorization conditions and convergence rates for Markov chains. J. Amer. Statist. Association 90, 558-566.
    • (1995) J. Amer. Statist. Association , vol.90 , pp. 558-566
    • Rosenthal, J.S.1
  • 33
    • 56949096369 scopus 로고    scopus 로고
    • Explicit error bounds for lazy reversible Markov chain Monte Carlo
    • D. Rudolf (2008): Explicit error bounds for lazy reversible Markov chain Monte Carlo. J. of Complexity. 25, 11-24.
    • (2008) J. of Complexity , vol.25 , pp. 11-24
    • Rudolf, D.1
  • 34
    • 77249126849 scopus 로고    scopus 로고
    • On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors
    • V. Roy, J.P. Hobert (2010): On Monte Carlo methods for Bayesian multivariate regression models with heavy-tailed errors. J. Multivariate Anal. 101, 1190-1202.
    • (2010) J. Multivariate Anal , vol.101 , pp. 1190-1202
    • Roy, V.1    Hobert, J.P.2
  • 35
    • 0034381555 scopus 로고    scopus 로고
    • How to couple from the past using a read-once source of randomness
    • D.B. Wilson (2000): How to couple from the past using a read-once source of randomness. Random Structures Algorithms 16 (1), 85-113.
    • (2000) Random Structures Algorithms , vol.16 , Issue.1 , pp. 85-113
    • Wilson, D.B.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.