Free Access
| Issue |
Genet. Sel. Evol.
Volume 32, Number 2, March-April 2000
|
|
|---|---|---|
| Page(s) | 143 - 163 | |
| DOI | https://doi.org/10.1051/gse:2000111 | |
References
- 1
- Anderson T.W., An introduction to multivariate statistical analysis, J. Wiley and Sons, New York, 1984.
- 2
- Anderson D.A., Aitkin M.A., Variance component models with binary response: interviewer variability, J. R. Stat. Soc. B 47 (1985) 203-210.
- 3
- Bertrand J.K., Benyshek L.L., Variance and covariance estimates for maternally influenced beef growth traits. J. Anim. Sci. 64 (1987) 728-734.
- 4
- Dempster A.P., Laird N.M., Rubin D.B., Maximum likelihood from incomplete data via the EM algorithm, J. R. Stat. Soc. B 39 (1977) 1-38.
- 5
- Diggle P.J., Liang K.Y., Zeger S.L., Analysis of longitudinal data, Oxford Science Publications, Clarendon Press, Oxford, 1994.
- 6
- Foulley J.L., Heteroskedastic threshold models with applications to the analysis of calving difficulties, Interbull Bulletins 18 (1998) 3-11.
- 7
- Foulley J.L., Quaas R.L., Heterogeneous variances in Gaussian linear mixed models, Genet. Sel. Evol. 27 (1995) 211-228.
- 8
- Foulley J.L., Quaas R.L., Than d'Arnoldi C., A link function approach to heterogeneous variance components, Genet. Sel. Evol. 30 (1998) 27-43.
- 9
- Foulley J.L., Jaffrezic F., Robert-Granié C., EM-REML estimation of covariance parameters in Gaussian mixed models for longitudinal data analysis, Genet. Sel. Evol. 32 (2000), 129-141.
- 10
- Gilmour A.R., Thompson R, Cullis B.R., Average information REML: an efficient algorithm for variance component parameter estimation in linear mixed models, Biometrics 51 (1995) 1440-1450.
- 11
- Hartley H.O., Rao J.N.K., Maximum likelihood estimation for the mixed analysis of variance model, Biometrika 54 (1967) 93-108.
- 12
- Harville D.A., Maximum likelihood approaches to variance component estimation and related problems, J. Am. Stat. Assoc. 72 (1977) 320-338.
- 13
- Henderson C.R., Sire evaluation and genetic trends, in: Proceedings of the animal breeding and genetics symposium in honor of Dr J Lush, American society of animal science-American dairy science association, Champaign, 1973, pp. 10-41.
- 14
- Henderson C.R., Applications of linear models in animal breeding, University of Guelph, Guelph, 1984.
- 15
- Johnson D.L., Thompson R., Restricted maximum likelihood estimation of variance components for univariate animal models using sparse matrix techniques and average information, J. Dairy Sci. 78 (1995) 449-456.
- 16
- Laird N.M., Ware J.H., Random effects models for longitudinal data, Biometrics 38 (1982) 963-974.
- 17
- Lindström M.J., Bates D.M., Newton-Raphson and EM algorithms for linear mixed effects models for repeated measures data, J. Am. Stat. Assoc. 83 (1988) 1014-1022.
- 18
- Littell R.C., Milliken G.A., Stroup W.W., Wolfinger R.D., SAS System for mixed models, SAS Institute Inc, Cary, NC, USA, 1996.
- 19
- Little R.J.A., Rubin D.B., Statistical analysis with missing data, J. Wiley and Sons, New York, 1977.
- 20
- Liu C., Rubin D.B., The ECME algorithm: a simple extension of EM and ECM with fast monotone convergence, Biometrika 81 (1994) 633-648.
- 21
- Liu C., Rubin D.B.,Wu Y.N., Parameter expansion to accelerate EM: The PX- EM algorithm, Biometrika 85 (1998) 755-770.
- 22
- Longford N.T., Random coefficient models, Clarendon Press, Oxford, 1993.
- 23
- Meng X.L., van Dyk D.A., The EM algorithm - an old song sung to a fast new tune (with discussion), J. R. Stat. Soc. B 59 (1997) 511-567.
- 24
- Meng X.L., van Dyk D.A., Fast EM-type implementations for mixed effects models, J. R. Stat. Soc. B 60 (1998) 559-578.
- 25
- Meyer K., An average information restricted maximum likelihood algorithm for estimating reduced rank genetic covariance matrices or covariance functions for animal models with equal design matrices, Genet. Sel. Evol. 29 (1997) 97-116.
- 26
- Misztal I., Comparison of computing properties of derivative and derivative- free algorithms in variance component estimation by REML, J. Anim. Breed. Genet. 111 (1994) 346-352.
- 27
- Patterson H.D., Thompson R., Recovery of interblock information when block sizes are unequal, Biometrika 58 (1971) 545-554.
- 28
- Pothoff R.F., Roy S.N., A generalized multivariate analysis of variance model useful especially for growth curve problems, Biometrika 51 (1964) 313-326.
- 29
- Quaas R.L., REML Note book, Mimeo, Cornell University, Ithaca, New York, 1992.
- 30
- Schaeffer L.R., Dekkers J.C.M., Random regressions in animal models for test-day production in dairy cattle, in: Proceedings of the 5th World Congress on Genetics Applied to Livestock Production 18 (1994) 443-446.
- 31
- Searle S.R., Matrix algebra useful for statistics, John Wiley & Sons, New York, 1982.
- 32
- van Dyk D.A., Fitting mixed-effects models using efficient EM-type algorithms, J. Comp. Graph. Stat. (2000) accepted.
- 33
- Verbeke G., Molenberghs G., Linear mixed models in practice, Springer Verlag, New York, 1997.
- 34
- Vonesh E.F., Carter R.L., Mixed-effects non linear regression for unbalanced repeated measures, Biometrics 48 (1992) 1-17.
- 35
- Wolfinger R.D., Tobias R.D., Joint estimation of location, dispersion, and random effects in robust design, Technometrics 40 (1998) 62-71.
Abstract
Copyright INRA, EDP Sciences