Open Access
Issue |
Genet. Sel. Evol.
Volume 40, Number 1, January-February 2008
|
|
---|---|---|
Page(s) | 3 - 24 | |
DOI | https://doi.org/10.1051/gse:2007032 | |
Published online | 21 December 2007 |
References of
Genet. Sel. Evol. 40 (2008) 3-24
- Boyd S., Vandenberghe L., Convex Optimization, Cambridge University Press (2004).
- Cullis B.R., Smith A.B., Thompson R., Perspectives of ANOVA, REML and a general linear mixed model, in: Methods and Models in Statistics in Honour of Professor John Nelder, FRS, Imperial College Press, London, 2004, pp. 53-94.
- Dempster A.P., Laird N.M., Rubin D.B., Maximum likelihood from incomplete data via the EM algorithm, J. Roy. Stat. Soc. B 39 (1977) 1-39.
- Dennis J.E., Schnabel R.B., Numerical methods for Unconstrained Optimization and Nonlinear Equations, SIAM Classics in Applied Mathematics, Society for Industrial and Applied Mathematics, Philadelphia, 1996.
- Forsgren A., Gill P.E., Murray W., Computing modified Newton directions using a partial Cholesky factorization, SIAM J. Sci. Statist. Comp. 16 (1995) 139-150 [CrossRef].
- Foulley J.L., van Dyk D.A, The PX-EM algorithm for fast stable fitting of Henderson's mixed model, Genet. Sel. Evol. 32 (2000) 143-163 [CrossRef] [PubMed] [EDP Sciences].
- Groeneveld E., A reparameterisation to improve numerical optimisation in multivariate REML (co)variance component estimation, Genet. Sel. Evol. 26 (1994) 537-545 [CrossRef] [EDP Sciences].
- Harville D.A., Maximum likelihood approaches to variance component estimation and related problems, J. Amer. Stat. Ass. 72 (1977) 320-338 [CrossRef].
- Harville D.A., Matrix Algebra from a Statistician's Perspective, Springer Verlag, 1997.
- Henderson C.R., A simple method for computing the inverse of a numerator relationship matrix used in prediction of breeding values, Biometrics 32 (1976) 69-83 [CrossRef].
- Henderson C.R., Estimation of variances and covariances under multiple trait models, J. Dairy Sci. 67 (1984) 1581-1589.
- Jamshidian M., Jennrich R.I, Conjugate gradient acceleration of the EM algorithm, J. Amer. Stat. Ass. 88 (1993) 221-228 [CrossRef].
- Jamshidian M., Jennrich R.I., Acceleration of the EM algorithm using Quasi-Newton methods, J. Roy. Stat. Soc. B 59 (1997) 569-587 [CrossRef].
- Jennrich R.I., Sampson P.F., Newton-Raphson and related algorithms for maximum likelihood variance component estimation, Technometrics 18 (1976) 11-17 [CrossRef] [MathSciNet].
- Jennrich R.I., Schluchter M.D., Unbalanced repeated-measures models with structured covariance matrices, Biometrics 42 (1986) 805-820 [CrossRef] [PubMed] [MathSciNet].
- Kirkpatrick M., Meyer K., Simplified analysis of complex phenotypes: Direct estimation of genetic principal components, Genetics 168 (2004) 2295-2306 [CrossRef] [PubMed].
- Laird N., Lange N., Stram D., Maximum likelihood computations with repeated measures: applications of the EM algorithm, J. Amer. Stat. Ass. 82 (1987) 97-105 [CrossRef].
- Lange K., A gradient algorithm locally equivalent to the EM algorithm, J. Roy. Stat. Soc. B 57 (1995) 425-438.
- Lindstrom M.J., Bates D.M., Newton-Raphson and EM algorithms for linear mixed-effects models for repeated-measures data, J. Amer. Stat. Ass. 83 (1988) 1014-1022 [CrossRef].
- Liu C., Rubin D.B., Wu Y.N., Parameter expansions to accelerate EM: The PX-EM algorithm, Biometrika 85 (1998) 755-770 [CrossRef] [MathSciNet].
- McLachlan G.J., Krishnan T., The EM algorithm and extensions, Wiley Series in Probability and Statistics, Wiley, New York, 1997.
- Meilijson I., A fast improvement of the EM algorithm on its own terms, J. Roy. Stat. Soc. B 51 (1989) 127-138.
- Meng X.L., van Dyk D., The EM algorithm - an old folk-song sung to a new fast tune, J. Roy. Stat. Soc. B 59 (1997) 511-567 [CrossRef].
- Meng X.L., van Dyk D., Fast EM-type implementations for mixed-effects models, J. Roy. Stat. Soc. B 60 (1998) 559-578 [CrossRef].
- Meyer K., Random regressions to model phenotypic variation in monthly weights of Australian beef cows, Livest. Prod. Sci. 65 (2000) 19-38 [CrossRef].
- Meyer K., Advances in methodology for random regression analyses, Austr. J. Exp. Agric. 45 (2005a) 847-858 [CrossRef].
- Meyer K., Genetic principal components for live ultra-sound scan traits of Angus cattle, Anim. Sci. 81 (2005b) 337-345 [CrossRef].
- Meyer K., PX
AI: algorithmics for better convergence in restricted maximum likelihood estimation, CD-ROM Eighth World Congr. Genet. Appl. Livest. Prod., August 13-18 2006, Belo Horizonte, Brasil, Communication No. 24-15.
- Meyer K., Kirkpatrick M., Restricted maximum likelihood estimation of genetic principal components and smoothed covariance matrices, Genet. Sel. Evol. 37 (2005) 1-30 [CrossRef] [PubMed] [EDP Sciences].
- Meyer K., Kirkpatrick M., A note on bias in reduced rank estimates of covariance matrices, Proc. Ass. Advan. Anim. Breed. Genet. 17 (2007) 154-157.
- Meyer K., Smith S.P., Restricted maximum likelihood estimation for animal models using derivatives of the likelihood, Genet. Sel. Evol. 28 (1996) 23-49 [CrossRef] [EDP Sciences].
- Meyer K., Carrick M.J., Donnelly B.J.P., Genetic parameters for growth traits of Australian beef cattle from a multi-breed selection experiment, J. Anim. Sci. 71 (1993) 2614-2622 [PubMed].
- Neumaier A., Groeneveld E., Restricted maximum likelihood estimation of covariance components in sparse linear models, Genet. Sel. Evol. 30 (1998) 3-26 [CrossRef] [EDP Sciences].
- Ng S.K., Krishnan T., McLachlan G.J., The EM algorithm, in: Gentle J.E., Härdle W., Mori Y., (Eds.), Handbook of Computational Statistics, vol. I, Springer Verlag, New York, 2004, pp. 137-168.
- Nocedahl J., Wright S.J., Numerical Optimization, Springer Series in Operations Research, Springer Verlag, New York, Berlin Heidelberg, 1999.
- Pinheiro J.C., Bates D.M., Unconstrained parameterizations for variance-covariance matrices, Stat. Comp. 6 (1996) 289-296 [CrossRef].
- Schnabel R.B., Estrow E., A new modified Cholesky factorization, SIAM J. Sci. Statist. Comp. 11 (1990) 1136-1158 [CrossRef].
- Thompson R., Meyer K., Estimation of variance components: What is missing in the EM algorithm? J. Stat. Comp. Simul. 24 (1986) 215-230 [CrossRef].
- Thompson R., Cullis B.R., Smith A.B., Gilmour A.R., A sparse implementation of the Average Information algorithm for factor analytic and reduced rank variance models, Austr. New Zeal. J. Stat. 45 (2003) 445-459 [CrossRef].
- Thompson R., Brotherstone S., White I.M.S., Estimation of quantitative genetic parameters, Phil. Trans. R. Soc. B 360 (2005) 1469-1477 [CrossRef].
- van Dyk D.A., Fitting mixed-effects models using efficient EM-type algorithms, J. Comp. Graph. Stat. 9 (2000) 78-98 [CrossRef].