BIE5781 - Modelagem Estatística para Ecologia e Recursos Naturais

A Resolução 5213 da Reitoria da USP permite que professores disponibilizem artigos e partes de livros adotados para uso estrito nas atividades de sua disciplina, apenas pelos alunos regularmente inscritos nela.

• Hilborn, R. & Mangel, M. (1997). The Ecological Detective – Confronting Models with Data. Princeton, Princeton University Press.
  • Capítulo 1: An Ecological Scenario and the Tools of the Ecological Detective.

• Johnson, J. B. & Omland, K. S. (2004). Model selection in ecology and evolution. Trends in Ecology and Evolution 19:101-108 pdf

• Hilborn, R. & Mangel, M. (1997). The Ecological Detective – Confronting Models with Data. Princeton, Princeton University Press.
  • Capítulo 2: Alternative Views of the Scientific Method and Modeling.

• Probability and stochastic distributions for ecological modeling. Capítulo 4, itens 4.4, e 4.5.1 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.

• Probability and stochastic distributions for ecological modeling. Capítulo 4, itens 4.1, 4.2, 4.3 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.

• Random variables and probability distributions. Cap.2 de Gotelli, N.J. & Ellison, A.M. 2004. A primer of ecological statistics. Sinauer.

• Otto, S. P. & Day, T. (2007). A biologist's guide to mathematical modelling in ecology and evolution. Princenton, Princenton University Press.
  • Capítulo 3: Probability Theory

• Probability and stochastic distributions for ecological modeling. Capítulo 4, item 4.5.2 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.

• Randon variables and probability distributions. Cap.2 de Gotelli, N.J. & Ellison, A.M. 2004. A primer of ecological statistics. Sinauer.

• Otto, S. P. & Day, T. (2007). A biologist's guide to mathematical modelling in ecology and evolution. Princenton, Princenton University Press.
  • Capítulo 3: Probability Theory

• Batista, J.L.F. 2009 Verossimilhança e Máxima Verossimilhança.

• Batista, J.L.F. 2014 Biometria Florestal segundo o Axioma da Verossimilhança. ESALQ-USP, Tese de Livre Docência, 391p.
• Likelihood and all that. capítulo 6 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.
• The Concept of Likelihood , cap.2 de: Edwards, A.W.F., 1992 Likelihood. Baltimore: John Hopkins University Press.
• Hobbs, N.T. & Hilborn, R. (2006). Alternatives to statistical hypothesis testing in ecology: A guide to self-teaching. Ecological Applications: 16(1): 5-19.
  • artigo
  • Apêndice A

• Likelihood and All That, seções 6.1 a 6.2.1.2 do Capítulo 6 de: Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.

• Anderson, D. R. (2008). Model based inference in the life sciences: a primer on evidence. New York, Springer.
  • cap.2
  • cap.3

• Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.:
  • Cap.6 - Likelihood and all that, seção 6.3.1
  • Cap.9 - Standard Statistics Revisited, seção 9.4

• Crawley, M.J. 2007. The R Book. New York, Wiley.
  • cap.13 - Generalized Linear Models
  • cap.14 - Count Data
  • cap.16 - Proportion Data

• Standard Statistics Revisited, seções 9.1 a 9.3, capítulo 9 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.

• Likelihood and least squares theory. Seção 1.2.2 do Cap.1 de Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical-Theoretic Approach, 2nd ed. New York, Springer-Verlag.

• Information and likelihood theory. Cap.2 de Burnham, K. P., & Anderson, D. R. (2002). Model Selection and Multimodel Inference: A Practical-Theoretic Approach, 2nd ed. New York, Springer-Verlag.

• Burnham, K.P.; Anderson, D.R. 2001 Kullback-Leibler information as a basis for strong inference in ecological studies. Wildlife Research, v.28, p.111-119.

• Royall, R. M. (2007) The likelihood paradigm for statistical evidence. In: The nature of scientific evidence (eds. ML Taper and SR Lele), University of Chicago Press, pp 119–152. pdf
• Lewin-Koh N., Taper, M. L. & Lele, S. R. (2004). A brief tour of statistical concepts. In: The nature of scientific evidence (eds. ML Taper and SR Lele), University of Chicago Press, pp 3 -16. pdf.

• Sober, E. 2008. Evidence and Evolution: the logic behind the science. Cambridge, Cambridge University Press. cap.1 - Evidence.
• "Likelihood": Uma palestra de A. W. F. Edwards.
• Berger, J.O. & Wolpert, R.L. 1984. The likelihood principle.Lecture Notes–IMS Monograph Series, Volume 6.

• Optimization and All That. Capítulo 7 de:Bolker, B.M. 2008 Ecological Models and Data in R Princeton: Princeton University Press.