Bayesian analysis of growth curves with AR(1) dependence |
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| Institution: | 1. Department of Animal Science, Federal University of Rio Grande do Sul (UFRGS), Bento Gonçalves Avenue, 7712, 91540-000 Porto Alegre, Rio Grande do Sul, Brazil;2. Department of Animal Science, Federal University of Rio Grande do Sul (UFRGS), Bento Gonçalves Avenue, 7712, 91540-000 Porto Alegre, Rio Grande do Sul, Brazil;3. Brazilian Agricultural Research Corporation (Embrapa), Embrapa Dairy Cattle– Rua Eugênio do Nascimento, 610 - Dom Bosco CEP, 36038-330 Juiz de Fora, MG, Brazil;4. Biochemistry Department, Health Basic Sciences Institute, Federal University of Rio Grande do Sul, Rua Ramiro Barcelos, 2600, 90035-003 Porto Alegre, Rio Grande do Sul, Brazil;5. Department of Animal Science, Federal University of Rio Grande do Sul (UFRGS), Avenida Bento Gonçalves, 7712, 91540-000 Porto Alegre, Rio Grande do Sul, Brazil;1. Facultad de Medicina Veterinaria y Zootecnia, Universidad Autónoma de Sinaloa, Blvd. San Ángel s/n, Fraccionamiento San Benito 80246, Culiacán, Sinaloa, México;;2. Departamento de Zootecnia, Universidad Autónoma de Chapingo, Carretera Federal México-Texcoco Km 38.5, CP 56230 Texcoco, México;;3. Instituto de Investigaciones en Ciencias Veterinarias, Universidad Autónoma de Baja California, Km 4.5 Carretera Mexicali-San Felipe, CP 21386, Mexicali, Baja California, México;;4. Department of Animal Science, University of California–Davis, Davis 95616; and;5. Departamento de Ciencias Naturales y Exactas, Universidad Autónoma de Occidente, Unidad regional Guasave CP 81049, Sinaloa, México |
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| Abstract: | In this paper we consider Bayesian analysis of the generalized growth curve model when the covariance matrix Σ = σ2C where C = (ϱi − j), σ2 > 0 and −1 < ϱ < 1 are unknown. We consider both parameter estimation and prediction of future values. Results are illustrated with real and simulated data. |
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