Parameter estimation of factors affecting milk yield in a multicollinearity by Bayesian Regression method
DOI:
https://doi.org/10.29329/JofBS.2021.348.05Keywords:
Bayesian regression, Multicollinearity, Milk yieldAbstract
The regression analysis determines the relationship model between dependent and independent variables. In this study, the body weight, milking time, milk yield and environmental factors obtained from 42 dairy cattle were used for internal and external temperatures. In this study, the Bayesian Regression method was used to estimate milk yield parameters in case of multicollinearity. According to the results, it was seen that Bayesian method can be applied successfully in the field of animal husbandry. It is thought that the use of this study for dairy cattle in other agricultural areas will be useful for better evaluation of the data obtained.
References
Atkinson, A. C. (2000). Robust diagnostic regression analysis. McGraw-Hill Comp.
Breusch, T. S. (1978). Testing for Autocorrelation in Dynamic Linear Models. Australian Economic Papers, 17(31), 334-355. https://doi.org/10.1111/j.1467-8454.1978.tb00635.x
Draper, N. R., & Smith, H. (1981). Applied regression analysis (2nd ed.). John Wiley & Sons.
Durbin, J. (1970). Testing for Serial Correlation in Least Squares Regression when some of the Regressors are Lagged Dependent Variables. Econometrica, 38(3), 410-421. https://doi.org/10.2307/1909547
Erdem, H., Atasever, S., & Kul, E. (2007). Gökhöyük Tarim İşletmesinde Yetiştirilen Siyah Alaca Sığırların Süt ve Döl Verim Özellikleri 2. Döl Verim Özellikleri. Ondokuzmayıs Üniversitesi Ziraat Fakültesi Dergisi, 22(1), 47-54. (in Turkish)
Ferreira, W. J., Texeira, N. M., Torres, R. de A., & da Silva, M. B. (2002). Utilização da Produção de Leite No Dia do Controle na Avaliação Genéticaem Gado de Leite - Uma Revisão. Archivos Latinoamericanos de Producción Animal, 10(1), 46-53. (in Spanish)
Jensen, J. (2001). Genetic Evaluation of Dairy Cattle Using Test-Day Models. Journal of Dairy Science, 84(12), 2803-2812. https://doi.org/10.3168/jds.S0022-0302(01)74736-4
Leamer, E. E. (1973). Multicollinearity: A Bayesian Interpretation. The Rewiev of Economics and Statistics, 55(3), 371-380. https://doi.org/10.2307/1927962
Ljung, G. M., & Box, G. E. P. (1978). On a Measure of Lack of Fit in Time Series Models. Biometrika, 65(2), 265-270. https://doi.org/10.1093/biomet/65.2.297
Montgomery, D. C., & Peck, E. A. (1992). Introduction to linear regression analysis. John Wiley & Sons.
Rao, C. R. (1973). Linear statistical inference and its application (2nd ed.). Wiley.
Rekaya, R., Carbaño, M. J., & Toro, M. A. (1999). Use of Test Day Yield for The Genetic Evaluation of Production Traits in Holstein-Friesian Cattle. Livestock Production Science, 57(3), 203-217. https://doi.org/10.1016/S0301-6226(98)00181-X
Vila, J. P., Wagner, V., & Neveu, P. (2000). Bayesian Nonlinear Model Selection and Neural Networks: A Conjugate Prior Approach. IEEE Transactions on Neural Networks, 11(2), 265-78. https://doi:10.1109/72.838999
Visscher, P. M., & Goddard, M. E. (1995). Genetic Parameters for Milk Yield, Survival, Workability, and Type Traits for Australian Dairy Cattle. Journal of Dairy Science, 78(1), 205-220. https://doi.org/10.3168/jds.S0022-0302(95)76630-9
Zellner, A. (1971). An introduction to Bayesian inference in econometrics. John Wiley.
