Free Access
Issue |
Genet. Sel. Evol.
Volume 35, Number 5, September-October 2003
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Page(s) | 489 - 512 | |
DOI | https://doi.org/10.1051/gse:2003036 |
References
- Albert J.H., Chib S., Bayesian analysis of binary and polychotomous response data, J. Am. Stat. Assoc. 88 (1993) 669-679.
- Albert J., Chib S., Bayesian residual analysis for binary response regression models, Biometrika 82 (1995) 747-759.
- Bennett G.L., Gregory K.E., Genetic (co)variances for calving difficulty score in composite and parental populations of beef cattle. I. Calving difficulty score, birth weight, weaning weight, and postweaning gain, J. Anim. Sci. 79 (2001) 45-51.
- Berger P.J., Genetic prediction for calving ease in the United States: Data, models, and use by the dairy industry, J. Dairy Sci. 77 (1994) 1146-1153.
- Bertrand J.K., Wiggans G.R., Validation of data and review of results from genetic evaluation systems for US beef and dairy cattle, in: Proceedings of the 6th World Congress on Genetics Applied to Livestock Production, 11-16 January, University of New England, Armidale, NSW, Australia, 1998, Vol. 27, pp. 327-330.
- Bink M.C.A.M., Quaas R.L., van Arendonk J.A.M., Bayesian estimation of dispersion parameters with a reduced animal model including polygenic and QTL effects, Genet. Sel. Evol. 30 (1998) 103-125.
- Carnier P., Albera A., Dal Zotto R., Groen A.F., Bona M., Bittante G., Genetic parameters for direct and maternal calving performance over parities in Piemontese cattle, J. Anim. Sci. 78 (2000) 2532-2539.
- Chen M-H., Dey D.K., Bayesian analysis for correlated ordinal data models, in: Dey D.K., Ghosh S.K., Mallick B.K. (Eds.), Generalized linear models: A Bayesian perspective, Marcel Dekker, New York, 2000, pp. 133-158.
- Chib S., Marginal likelihood from the Gibbs output, J. Am. Stat. Assoc. 90 (1995) 773-795.
- Chib S., Greenberg E., Understanding the Metropolis Hastings algorithm, Am. Stat. 49 (1995) 327-335.
- Cowles M.K., Accelerating Monte Carlo Markov Chain convergence for cumulative link generalized linear models, Stat. Comp. 6 (1996) 101-111.
- Dempster A.P., The direct use of likelihood for significance testing, Stat. Comp. 7 (1997) 247-252.
- Emanuelson U., Fikse F., Banos G., Impact of national genetic evaluation models on international comparisons, in: Computational Cattle Breeding '99, 18-20 March 1999, Tuusula, Finland (http://www.csc.fi/ttn/ccb99/).
- Gelfand A.E., Model determination using sampling-based methods, in: Gilks W.R., Richardson S., Spiegelhalter D.J. (Eds.), Markov Chain Monte Carlo in practice, Chapman & Hall, New York, 1996, pp. 145-162.
- Gelfand A.E., Ghosh S.K., Model choice: A minimum posterior predictive loss approach, Biometrika 85 (1998) 1-11.
- Geyer C.J., Practical Markov chain Monte-Carlo (with discussion), Stat. Sci. 7 (1992) 467-511.
- Gianola D., Foulley J.L., Sire evaluation for ordered categorical data with a threshold model, Génét. Sél. Évol. 15 (1983) 201-224.
- Gianola D., Sorensen D.A., A mixed effects threshold model with t-distributions. Book of Abstracts of the 47th Annual Meeting of the European Association for Animal Production, 1996, Wageningen Press, the Netherlands, p. 47.
- Henderson C.R., Inverse of a matrix of relationships due to sires and maternal grandsires in an inbred population, J. Dairy Sci. 59 (1976) 1585-1588.
- Heringstad B., Rekaya R., Gianola D., Klemetsdal G., Weigel K.A., Bayesian analysis of liability of clinical mastitis in Norwegian cattle with a threshold model: Effects of data sampling method and model specification, J. Dairy Sci. 84 (2001) 2337-2346.
- Jensen J., Wang C.S., Sorensen D.A., Gianola D., Bayesian inference on variance and covariance components for traits influenced by maternal and direct genetic effects, using the Gibbs sampler, Acta Agric. Scand. A-An. 44 (1994) 193-201.
- Johnson V.E., Albert J.H., Ordinal data modeling, Springer, New York, 1999.
- Kizilkaya K., Banks B.D., Carnier P., Albera A., Bittante G., Tempelman R.J., Bayesian inference strategies for the prediction of genetic merit using threshold models with an application to calving ease scores in Italian Piemontese cattle, J. Anim. Breed. Genet. 119 (2002) 209-220.
- Lange K.L., Little R.J.A., Taylor J.M.G., Robust statistical modeling using the t-distribution, J. Am. Stat. Assoc. 84 (1989) 881-896.
- Luo M.F., Boettcher P.J., Dekkers J.C.M., Schaeffer L.R., Bayesian analysis for estimation of genetic parameters of calving ease and stillbirth for Canadian Holsteins, J. Dairy Sci. 82 (1999) 1848.
- Luo M.F., Boettcher P.J., Schaeffer L.R., Dekkers J.C.M., Bayesian inference for categorical traits with an application to variance components estimation, J. Dairy Sci. 84 (2001) 694-704.
- Manfredi E.J., San Cristobal M., Foulley J.L., Some factor affecting the estimation of genetic parameters for cattle dystocia under a threshold model, Anim. Prod. 53 (1991) 151-156.
- Manfredi E.J., Ducrocq V., Foulley J.L., Genetic analysis of dystocia in dairy cattle, J. Dairy Sci. 74 (1991) 1715-1723.
- Mayer M., Inequality of maximum a posteriori estimators with equivalent sire and animal models for threshold traits, Genet. Sel. Evol. 27 (1995) 423-435.
- McGuirk B.J., Going I., Gilmour A.R., The genetic evaluation of beef sires used for crossing with dairy cows in the UK. 2. Genetic parameters and sire merit predictions for calving survey traits, Anim. Sci. 66 (1998) 47-54.
- McGuirk B.J., Going I., Gilmour A.R., The genetic evaluation of UK Holstein Friesian sires for calving ease and related traits, Anim. Sci. 68 (1999) 413-422.
- Müller P., A generic approach to posterior integration and Gibbs sampling, Technical Report, Purdue University, 1993.
- Newton M.A., Raftery A.E., Approximate Bayesian inference with the weighted likelihood bootstrap, J. R. Stat. Soc. Ser. B 56 (1994) 3-48.
- Raftery A.E., Hypothesis testing and model selection, in: Gilks W.R., Richardson S., Spiegelhalter D.J. (Eds.), Markov Chain Monte Carlo in practice, Chapman & Hall, New York, 1996, pp. 163-187.
- Rekaya R., Weigel K.A., Gianola D., Application of a structural model for genetic covariances in international dairy sire evaluations, J. Dairy Sci. 84 (2001) 1525-1530.
- Rosa G.J.M., Robust mixed linear models in quantitative genetics: Bayesian analysis via Gibbs sampling, in: Proceedings of International Symposium on Animal Breeding and Genetics, 21-24 September 1999, Brazil, pp. 133-159.
- San Cristobal-Gaudy M., Bodin L., Elsen J-.M., Chevalet C., Genetic components of litter size variability in sheep, Genet. Sel. Evol. 33 (2001) 249-271.
- Satagopan J.M., Newton M.A., Raftery A.E., Easy estimation of normalizing constants and Bayes factors from posterior simulation: stabilizing the harmonic mean estimator, Technical Report 1028, Department of Statistics, 2001. http://www.stat.wisc.edu/ newton/papers/abstracts/tr1028a.html.
- Sorensen D.A., Andersen S., Gianola D., Korsgaard I., Bayesian inference in threshold models using Gibbs sampling, Genet. Sel. Evol. 27 (1995) 229-249.
- Spiegelhalter D.J., Best N.G., Carlin B.P., van der Linde A., Bayesian measures of model complexity and fit (with discussion), J. R. Statist. Soc. B 64 (2002) 583-639.
- Stranden I., Gianola D., Attenuating effects of preferential treatment with Student-t mixed linear models: a simulation study, Genet. Sel. Evol. 30 (1998) 565-583.
- Stranden I., Gianola D., Mixed effects linear models with t-distributions for quantitative genetic analysis: a Bayesian approach, Genet. Sel. Evol. 31 (1999) 25-42.
- Tempelman R.J., Gianola D., A mixed effects model for overdispersed count data in animal breeding, Biometrics 52 (1996) 265-279.
- Uimari P., Thaller G., Hoeschele I., The use of multiple markers in a Bayesian method for mapping quantitative trait loci, Genetics 143 (1996) 1831-1842.
- van Dyk D.A., Meng X-L., The art of data augmentation (with discussion), J. Comp. Grap. Stat. 10 (2001) 1-50.
- Varona L., Misztal I., Bertrand J.K., Threshold-linear versus linear-linear analysis of birth weight and calving ease using an animal model. I. Variance component estimation, J. Anim. Sci. 77 (1999) 1994-2002.
- von Rohr P., Hoeschele I., Bayesian QTL mapping using skewed Student-t-distributions, Genet. Sel. Evol. 34 (2002) 1-21.
- Wang C.S., Rutledge J.J., Gianola D., Bayesian analysis of mixed linear models via Gibbs sampling with an application to litter size in Iberian pigs, Genet. Sel. Evol. 26 (1994) 91-115
- Wang C.S., Quaas R.L., Pollak E.J., Bayesian analysis of calving ease scores and birth weights, Genet. Sel. Evol. 29 (1997) 117-143.
- Zhu L., Carlin B.P., Comparing hierarchical models for spatio-temporally misaligned data using the deviance information criterion, Stat. Med. 19 (2000) 2265-2278.
Abstract
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