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Volumn 129, Issue 6, 2012, Pages 457-468

Employing a Monte Carlo algorithm in expectation maximization restricted maximum likelihood estimation of the linear mixed model

Author keywords

Convergence criterion; Monte Carlo sample size; Variance components

Indexed keywords

ALGORITHM; ANIMAL; ARTICLE; BREEDING; CATTLE; FEASIBILITY STUDY; MONTE CARLO METHOD; STATISTICAL MODEL;

EID: 84869166290     PISSN: 09312668     EISSN: 14390388     Source Type: Journal    
DOI: 10.1111/j.1439-0388.2012.01000.x     Document Type: Article
Times cited : (12)

References (27)
  • 1
    • 0033475053 scopus 로고    scopus 로고
    • Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm
    • Booth J.G., Hobert J.P. (1999) Maximizing generalized linear mixed model likelihoods with an automated Monte Carlo EM algorithm. J. R. Statist. Soc. B, 61, 265-285.
    • (1999) J. R. Statist. Soc. B , vol.61 , pp. 265-285
    • Booth, J.G.1    Hobert, J.P.2
  • 2
    • 0002241694 scopus 로고
    • The SEM algorithm: a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem
    • Celeux G., Diebolt J. (1985) The SEM algorithm: a probabilistic teacher algorithm derived from the EM algorithm for the mixture problem. Comp. Statist. Q., 2, 73-82.
    • (1985) Comp. Statist. Q. , vol.2 , pp. 73-82
    • Celeux, G.1    Diebolt, J.2
  • 3
    • 0033243858 scopus 로고    scopus 로고
    • Convergence of a stochastic approximation version of the EM algorithm
    • Delyon B., Lavielle M., Moulines E. (1999) Convergence of a stochastic approximation version of the EM algorithm. Ann. Statist., 27, 94-128.
    • (1999) Ann. Statist. , vol.27 , pp. 94-128
    • Delyon, B.1    Lavielle, M.2    Moulines, E.3
  • 4
    • 0002629270 scopus 로고
    • Maximum likelihood from incomplete data via the EM algorithm
    • Dempster A.P., Laird N.M., Rubin D.B. (1977) Maximum likelihood from incomplete data via the EM algorithm. J. R. Statist. Soc. B, 39, 1-38.
    • (1977) J. R. Statist. Soc. B , vol.39 , pp. 1-38
    • Dempster, A.P.1    Laird, N.M.2    Rubin, D.B.3
  • 5
    • 0034060090 scopus 로고    scopus 로고
    • The PX-EM algorithm for fast stable fitting of Henderson's mixed model
    • Foulley J.-L., van Dyk D.A. (2000) The PX-EM algorithm for fast stable fitting of Henderson's mixed model. Genet. Sel. Evol., 32, 143-163.
    • (2000) Genet. Sel. Evol. , vol.32 , pp. 143-163
    • Foulley, J.-L.1    van Dyk, D.A.2
  • 6
    • 0034830499 scopus 로고    scopus 로고
    • Alternative implementations of Monte Carlo EM algorithms for likelihood inference
    • García-Cortés L.A., Sorensen D. (2001) Alternative implementations of Monte Carlo EM algorithms for likelihood inference. Genet. Sel. Evol., 33, 443-452.
    • (2001) Genet. Sel. Evol. , vol.33 , pp. 443-452
    • García-Cortés, L.A.1    Sorensen, D.2
  • 9
    • 0029564551 scopus 로고
    • Average information REML: an efficient algorithm for variance parameter estimation in linear mixed models
    • Gilmour A., Thompson R., Cullis B. (1995) Average information REML: an efficient algorithm for variance parameter estimation in linear mixed models. Biometrics, 51, 1440-1450.
    • (1995) Biometrics , vol.51 , pp. 1440-1450
    • Gilmour, A.1    Thompson, R.2    Cullis, B.3
  • 10
    • 77957177451 scopus 로고
    • Monte Carlo estimation of variance component models for large complex pedigrees
    • Guo S.W., Thompson E.A. (1991) Monte Carlo estimation of variance component models for large complex pedigrees. IMA J. Math. Appl. Med. Biol., 8, 171-189.
    • (1991) IMA J. Math. Appl. Med. Biol. , vol.8 , pp. 171-189
    • Guo, S.W.1    Thompson, E.A.2
  • 11
    • 0842346732 scopus 로고    scopus 로고
    • Making REML computationally feasible for large data sets: use of Gibbs sampler
    • Harville D.A. (2004) Making REML computationally feasible for large data sets: use of Gibbs sampler. J. Stat. Comp. Sim., 74, 135-153.
    • (2004) J. Stat. Comp. Sim. , vol.74 , pp. 135-153
    • Harville, D.A.1
  • 12
    • 0040845224 scopus 로고
    • Estimation of variances and covariances under multiple trait model
    • Henderson C.R. (1984) Estimation of variances and covariances under multiple trait model. J. Dairy Sci., 67, 1581-1589.
    • (1984) J. Dairy Sci. , vol.67 , pp. 1581-1589
    • Henderson, C.R.1
  • 13
    • 77949834462 scopus 로고    scopus 로고
    • Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance
    • Hickey J.M., Veerkamp R.F., Calus M.P.L., Mulder H.A., Thompson R. (2009) Estimation of prediction error variances via Monte Carlo sampling methods using different formulations of the prediction error variance. Genet. Sel. Evol., 41, 23.
    • (2009) Genet. Sel. Evol. , vol.41 , pp. 23
    • Hickey, J.M.1    Veerkamp, R.F.2    Calus, M.P.L.3    Mulder, H.A.4    Thompson, R.5
  • 15
    • 84869198387 scopus 로고
    • Animal model estimation using simulated REML. In: Proceedings 4th World Congress on Genetics Applied to Livestock Production XIII: 472-475. Edinburgh, July 1990
    • Klassen D.J., Smith S.P. (1990) Animal model estimation using simulated REML. In: Proceedings 4th World Congress on Genetics Applied to Livestock Production XIII: 472-475. Edinburgh, 23-27 July 1990.
    • (1990) , pp. 23-27
    • Klassen, D.J.1    Smith, S.P.2
  • 16
    • 0035628553 scopus 로고    scopus 로고
    • Implementations of the Monte Carlo EM algorithm
    • Levine R.A., Casella G. (2001) Implementations of the Monte Carlo EM algorithm. J. Comp. Graph. Stat., 10, 422-439.
    • (2001) J. Comp. Graph. Stat. , vol.10 , pp. 422-439
    • Levine, R.A.1    Casella, G.2
  • 17
    • 2442599184 scopus 로고    scopus 로고
    • An automated (Markov chain) Monte Carlo EM algorithm
    • Levine R.A., Fan J. (2004) An automated (Markov chain) Monte Carlo EM algorithm. J. Stat. Comp. Sim., 74, 349-360.
    • (2004) J. Stat. Comp. Sim. , vol.74 , pp. 349-360
    • Levine, R.A.1    Fan, J.2
  • 18
    • 84891740814 scopus 로고    scopus 로고
    • Technical reference guide for MiX99, Release IV/2011. MTT Agrifood Research Finland
    • Lidauer M.H., Matilainen K., Mäntysaari E.A., Strandén I. (2011) Technical reference guide for MiX99, Release IV/2011. MTT Agrifood Research Finland. http://www.mtt.fi/BGE/Software/MiX99.
    • (2011)
    • Lidauer, M.H.1    Matilainen, K.2    Mäntysaari, E.A.3    Strandén, I.4
  • 20
    • 85014863826 scopus 로고
    • Restricted maximum likelihood estimates of variance components from multitrait sire models with large number of fixed effects
    • Mäntysaari E., Van Vleck L.D. (1989) Restricted maximum likelihood estimates of variance components from multitrait sire models with large number of fixed effects. J. Anim. Breed. Genet., 106, 409-422.
    • (1989) J. Anim. Breed. Genet. , vol.106 , pp. 409-422
    • Mäntysaari, E.1    Van Vleck, L.D.2
  • 21
    • 0031479575 scopus 로고    scopus 로고
    • Maximum likelihood algorithms for generalized linear mixed models
    • McCulloch C.E. (1997) Maximum likelihood algorithms for generalized linear mixed models. J. Am. Stat. Ass., 92, 162-170.
    • (1997) J. Am. Stat. Ass. , vol.92 , pp. 162-170
    • McCulloch, C.E.1
  • 22
    • 58549090692 scopus 로고    scopus 로고
    • Estimation in the probit normal model for binary outcomes using the SAEM algorithm
    • Meza C., Jaffrézic F., Foulley J.-L. (2009) Estimation in the probit normal model for binary outcomes using the SAEM algorithm. Comp. Stat. Data Anal., 53, 1350-1360.
    • (2009) Comp. Stat. Data Anal. , vol.53 , pp. 1350-1360
    • Meza, C.1    Jaffrézic, F.2    Foulley, J.-L.3
  • 23
    • 55949129116 scopus 로고    scopus 로고
    • Reliable computing in estimation of variance components
    • Misztal I. (2008) Reliable computing in estimation of variance components. J. Anim. Breed. Genet., 125, 363-370.
    • (2008) J. Anim. Breed. Genet. , vol.125 , pp. 363-370
    • Misztal, I.1
  • 24
    • 0036884552 scopus 로고    scopus 로고
    • Maximum likelihood inference for multivariate frailty models using an automated Monte Carlo EM algorithm
    • Ripatti S., Larsen K., Palmgren J. (2002) Maximum likelihood inference for multivariate frailty models using an automated Monte Carlo EM algorithm. Lifetime Data Anal., 8, 349-360.
    • (2002) Lifetime Data Anal. , vol.8 , pp. 349-360
    • Ripatti, S.1    Larsen, K.2    Palmgren, J.3
  • 25
    • 0033254742 scopus 로고    scopus 로고
    • Solving large mixed linear models using preconditioned conjugate gradient iteration
    • Strandén I., Lidauer M. (1999) Solving large mixed linear models using preconditioned conjugate gradient iteration. J. Dairy Sci., 82, 2779-2787.
    • (1999) J. Dairy Sci. , vol.82 , pp. 2779-2787
    • Strandén, I.1    Lidauer, M.2
  • 26
    • 84869185679 scopus 로고
    • Integrating best linear unbiased prediction and maximum likelihood estimation. In: Proceedings 5th World Congress on Genetics Applied to Livestock Production XVIII: 337-340. Guelph, August 1994
    • Thompson R. (1994) Integrating best linear unbiased prediction and maximum likelihood estimation. In: Proceedings 5th World Congress on Genetics Applied to Livestock Production XVIII: 337-340. Guelph, 7-12 August 1994.
    • (1994) , pp. 7-12
    • Thompson, R.1
  • 27
    • 84950432017 scopus 로고
    • A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms
    • Wei G., Tanner M. (1990) A Monte Carlo implementation of the EM algorithm and the poor man's data augmentation algorithms. J. Am. Stat. Ass., 85, 699-704.
    • (1990) J. Am. Stat. Ass. , vol.85 , pp. 699-704
    • Wei, G.1    Tanner, M.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.