×

An integrated approach between computing and mathematical modelling for cattle welfare in grazing systems. (English) Zbl 1527.62087

MSC:

62P12 Applications of statistics to environmental and related topics

Software:

R

References:

[1] Alves, B. J. R., Madari, B .E.&Boddey, R.M. Integrated crop-livestock-forestry systems: prospects for a sustainable agricultural intensification. Nutr Cycl Agroecosyst, 108 (2017), 1-4.
[2] Agresti, A. Categorical Data Analysis. John Wiley, New York (1990). · Zbl 0716.62001
[3] Akaike, H. A new look at the statistical model identification. IEEE transactions on automatic control, 19(6) (1974), 716-723. · Zbl 0314.62039
[4] Albright, J. L. Nutrition, feeding and calves: feeding behavior of dairy cattle. Journal of Dairy Science, 76 (1993), 485-498.
[5] Bayaga, A. Multinomial logistic regression: Usage and application in risk analysis. Journal of Applied Quantitative Methods, 5(2) (2010), 288-297.
[6] Broom, D. M. Animal welfare: concepts and measurement. Journal of Animal Science, 68 (1991), 4167-4175.
[7] Casella, G.&Berger, R. L. Statistical inference, vol 2. Duxbury Pacific Grove, CA (2002).
[8] Cox, D. R.&Snell, E. J. Analysis of Binary Data. Second edition: Chappman & Hall (1989). · Zbl 0729.62004
[9] Cressie, N.&Read, T. R. C. Multinomial goodness-of-fit tests. Journal of the Royal Statistical Society B, 46 (1984), 440-464. · Zbl 0571.62017
[10] de Oliveira, C. C., Alves, F. V., de Almeida, R. G., GamarraÉL. Villela, S. D. J.&de Almeida Martins, P. G. M. Thermal comfort indices assessed in integrated production systems in the brazilian savannah. Agroforestry Systems, (2018), 1-14.
[11] El-Habil, A. M. An application on multinomial logistic regression. Pakistan Journal of Statistics and Operation Research, 8(2) (2012), 271-291.
[12] Hoemers, D. W.&Lemeshow, S. Applied Logistic Regression. John Wiley, New York (2000). · Zbl 0967.62045
[13] Kichel, A. N., Bungenstab, D, J., Zimmer, A. H., Soares, C. O., Almeida, R., Bungenstab, D.&Almeida, R. Crop-livestock-forestry integration and the progress of the brazilian agriculture. In-tegrated crop-livestock-forestry systems, a Brazilian experience for sustainable farming. Embrapa, Brasilia, DF, Brazil (2014), p. 19-26.
[14] McFadden, D. Conditional logit analysis of qualitative choice behaviour. In: P. Zrembka (ed.), Frontiers in Econometrics. Academic Press (1973), p. 105-142.
[15] Menard, D. Proportional reduction of error (PRE). In: M. Lewis-Beck, A. Bryman, & T. Liao (Eds.), Encyclopedia of social science research methods. Thousand Oaks, CA: SAGE Publications,(2014), p. 877-878.
[16] Nagelkerke, N. J. D. A Note on a general definition of the coefficient of determination. Biometrika, 78 (1991), 691-692. · Zbl 0741.62069
[17] Pearson, K. Notes on regression and inheritance in the case of two parents. Proceedings of the Royal Society of London, 58 (1895), 240-242.
[18] Pezzopane, J., Bonani, W., Bosi, C., Fernandes da Rocha, E., De Campos Bernardi, A., Oliveira, P.,&De Faria Pedroso, A. Reducing competition in a crop-livestock-forest integrated system by thinning eucalyptus trees. Experimental Agriculture, 56(4) (2020), 574-586.
[19] R Developement Core Team (2018). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.
[20] Rossi, R. J. Mathematical Statistics : An Introduction to Likelihood Based Inference. New York: John Wiley & Sons (2018), p. 227. · Zbl 1407.62006
[21] Stigler, S. M. Francis Galton’s account of the invention of correlation. Statistical Science, 4(2) (1989), 73-79. · Zbl 0955.01506
[22] Thomas, W. Y. VGAM: Vector Generalized Linear and Additive Models. R package version 1.0-3, (2017). https://CRAN.R-project.org/package=VGAM.
[23] Schwarz, G. E. Estimating the dimension of a model. Annals of Statistics, 6 (1978), 461-464. · Zbl 0379.62005
[24] Stevens, J. Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum Associates (2007).
[25] Wald, A. Tests of statistical hypotheses concerning several parameters when the number of observations is large. Transactions of the American Mathematical society, 54(3) (1943), 426-482. · Zbl 0063.08120
[26] Trends Comput. Appl. Math., 22, N. 4 (2021)
[27] R. M. O. SANTOS, E. F. SARAIVA and R. R. SANTOS 643
[28] White, J. L. Logistic Regression Model Effectiveness: Proportional Chance Criteria and Proportional Reduction in Error. Journal of Contemporary Research in Education, 2(1) (2017), 4-10.
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.