References
- Akaike, H. 1973. Information theory and an extension of the maximum likelihood principle. In: 2nd Int. Symp. Inf. Theory (Ed. B. Petrov and F. Csaki). Akad. Kiado, Budapest. pp. 267-281.
- Albuquerque, L. G. and K. Meyer. 2001. Estimates of direct and maternal genetic effects for weights from birth to 600 days of age in Nelore cattle. J. Anim. Breed. Genet. 118:83-92. https://doi.org/10.1046/j.1439-0388.2001.00279.x
- Johnson, D. L. and R. Thompson. 1995. Restricted maximum likelihood estimation of variance components for univariate animal models using sparse matrix techniques and average information. J. Dairy Sci. 78:449-456. https://doi.org/10.3168/jds.S0022-0302(95)76654-1
- Kirkpatrick, M. and N. Heckman. 1989. A quantitative genetic model for growth, shape, and other infinite dimensional characters. J. Math. Biol. 27:429-450. https://doi.org/10.1007/BF00290638
- Kirkpatrick, M., D. Lofsvold and M. Bulmer. 1990. Analysis of the inheritance, selection and evolution of growth trajectories. Genetics 124:979-993.
- Kirkpatrick, M., W. G. Hill and R. Thompson. 1994. Estimating the covariance structure of traits during growth and aging, illustrated with lactation in dairy cattle. Genet. Res. 64:57-69. https://doi.org/10.1017/S0016672300032559
- Liu Wenzhong. 2001. ph D. thesis. China Agricultural University, Beijing, China.
- Liu Wenzhong, Zhang Yuan and Zhou Zhongxiao. 2001. Influences of different additional random effects on estimating covariance functions. Hereditas (Beijing) 23:317-320.
- Meyer, K. and W. G. Hill. 1997. Estimation of genetic and phenotypic covariance functions for longitudinal or 'repeated' records by restricted maximum likelihood. Livst. Prod. Sci. 47:185-200. https://doi.org/10.1016/S0301-6226(96)01414-5
- Meyer, K. 1998a. Estimating covariance functions for longitudinal data using a random regression model. Genet. Sel. Evol. 30:221-240. https://doi.org/10.1186/1297-9686-30-3-221
- Meyer, K. 1998b. Modeling 'repeated' records: covariance functions and random regression models to analyze animal breeding data. Proc. 6th World Congr. Genet. Appl. Livest. Prod. 25:517-520.
- Meyer, K. 1998c. 'DXMRR'-A program to estimate covariance functions for longitudinal data by restricted maximum likelihood. Proc. 6th World Congr. Genet. Appl. Livest. Prod. 27:465-466.
- Meyer, K. 1999. Estimates of direct and maternal genetic covariance functions for early growth of Australian beef cattle. 50th Ann. Meet. Eur. Assoc. Anim. Prod. Zurich. p. 296.
- Meyer, K. 2001. Estimates of direct and maternal covariance functions for growth of Australian beef calves from birth to weaning. Genet. Sel. Evol. 33:487-514. https://doi.org/10.1186/1297-9686-33-5-487
- Van der Werf, J., M. Goddard and K. Meyer. 1998. The use of covariance functions and random regression for genetic evaluation of milk production based on test day records. J. Dairy Sci. 81:3300-3308. https://doi.org/10.3168/jds.S0022-0302(98)75895-3
- Zhou Zhongxiao, Liu Wenzhong, Zhang Shaozeng, Zhang Yiming and Jia Yuzhi. 1999. Research on Shanxi lean-meat pig (Line SD-II) breeding. Proc. 10th Nat. Symp. Anim. Breed. Genet. pp. 401-404.
Cited by
- Genetic Parameters for Litter Size in Pigs Using a Random Regression Model vol.20, pp.2, 2007, https://doi.org/10.5713/ajas.2007.160
- Estimation of Covariance Functions for Growth of Angora Goats vol.22, pp.7, 2009, https://doi.org/10.5713/ajas.2009.70036