Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference solutions for activities¶ day 1a: Bayesian thinking¶ In [ ]: # function to calculate log-like of data D={0,1} given N={0,1} calcLogLikeNessie
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Bayesian statistics Introduction to Bayesian methods in ecology and evolution Matteo Fumagalli m.fumagalli@imperial.ac.uk Imperial College London February 17, 2020 Contents 1 Birds 1 2 Frogs 3 3 Ancient DNA 5 4 Extinctions 8 1 Birds You are in the Galapagos and you want to model the distribution of beak widths in Darwin finches. In the
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 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference day 2a: prior distributions¶ Intended Learning Outcomes¶ At the end of this part you will be able to: • describe the pros and cons of using different priors (e.g. elicited, conjugate, …); • evaluate the interplay between prior and posterior distributions, • calculate several quantities of interest
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ICES Journal of Marine Science (2017), 74(5), 1334–1343. doi:10.1093/icesjms/fsw231 Original Article Predicting ecosystem responses to changes in fisheries catch, temperature, and primary productivity with a dynamic Bayesian network model Neda Trifonova,1,* David Maxwell,2 John Pinnegar,2 Andrew Kenny,2 and Allan Tucker1 1Brunel University, Uxbridge UB8 3PH, UK 2CEFAS, Lowestoft NR33 0HT, UK *Corresponding author: tel: þ447532170322;
Bayesian statistics¶ Bayesian thinking¶ The eyes and the brain¶ Imagine I enter the classroom by telling you that I have just spotted the Loch Ness monster in the lake at Silwood Park campus (or Hyde Park).  What does this information tell you on the existence or not of Nessie? In the classic frequentist, or
 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference solutions for activities¶ day 1a: Bayesian thinking¶ In [ ]: # function to calculate log-like of data D={0,1} given N={0,1} calcLogLikeNessie
程序代写代做 Bayesian algorithm Bayesian network  Read More »
 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference part 3: prior distributions¶ Intended Learning Outcomes¶ At the end of this part you will be able to: • describe the pros and cons of using different priors (e.g. elicited, conjugate, …); • evaluate the interplay between prior and posterior distributions using R, • calculate several quantities
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 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference day 5b: ecological applications of Bayesian networks¶ Read one of the following papers provided in Readings folder: • Eklof_2013.pdf • Gaggiotti_2010.pdf • Trifonova_2017.pdf These studies propose the use of Bayen networks in the field of ecology (either theoretical or applied) and evolution. Write a short report (equivalent
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 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference day 2a: prior distributions¶ Intended Learning Outcomes¶ At the end of this part you will be able to: • describe the pros and cons of using different priors (e.g. elicited, conjugate, …), • evaluate the interplay between prior and posterior distributions, • calculate several quantities of interest
程序代写代做 Bayesian C flex graph Bayesian network  Read More »
 Bayesian methods in ecology and evolution¶ https://bitbucket.org/mfumagal/statistical_inference day 5a: Bayesian networks¶ Intended Learning Outcomes¶ At the end of this part you will be able to: • describe the concepts of conditional parameterisation and conditional independence, • implement a naive Bayes model, • calculate joint probabilities from Bayes networks, • appreciate the use of Bayes
程序代写代做 chain flex Bayesian graph Bayesian network data structure  Read More »