ONLINE COURSE Species distribution modelling with Bayesian statistics in R (SDMB01) This course will be delivered live
https://www.prstatistics.com/course/species-distribution-modelling-with-bayesian-statistics-in-r-sdmb01/ Course Overview: Bayesian Additive Regression Trees (BART) are a powerful machine learning technique with very promising potential applications in ecology and biogeography in general, and in species distribution modelling (SDM) in particular. Becasue BART models can generally provide a well-balanced performance regarding both main aspects of predictive accuracy, namely discrimination (i.e. distinguishing presence from absence localities) and calibration (i.e., having predicted probabilities reflect the species’ gradual occurrence frequencies) they are an effective method for handling marine mammal data. BART can generate accurate predictions without overfitting to noise or to particular cases in the data. As it is a cutting-edge technique in this field, BART is not yet routinely included in SDM workflows or in ensemble modelling packages. This course will include 1) an introduction or refresher on the essentials of the R language; 2) an introduction or refresher on species distribution modelling; 3) an overview of SDM methods of different complexity, including regression-based and machine-learning (both Bayesian and non-Bayesian) methods; 4) SDM building and block cross-validation focused on different aspects of model performance, including discrimination, classification, and calibration or reliability. We will use R packages ’embarcadero’, ‘fuzzySim’ and ‘modEvA’ to see how BART can perform well when all these aspects are equally important, as well as to identify relevant predictors, map prediction uncertainty, plot partial dependence curves with credible intervals, and map relative favourability regarding combined or individual predictors. Students will apply all these techniques to their own species distribution data, or to example data that will be provided during the course. email oliverhoo...@prstatistics.com with any enquiries or to request different payment options Introduction to statistics using R and Rstudio (IRRS02) 28 October 2020 - 29 October 2020 https://www.prstatistics.com/course/introduction-to-statistics-using-r-and-rstudio-irrs02/ Species distribution modelling with Bayesian statistics in R (SDMB01) 9 November 2020 - 13 November 2020 https://www.prstatistics.com/course/species-distribution-modelling-with-bayesian-statistics-in-r-sdmb01/ Introduction to Bayesian modelling with INLA (BMIN01) 9 November 2020 - 13 November 2020 https://www.prstatistics.com/course/introduction-to-bayesian-modelling-with-inla-bmin01/ Introduction to generalised linear models using R and Rstudio (IGLM02) 18 November 2020 - 19 November 2020 https://www.prstatistics.com/course/introduction-to-generalised-linear-models-using-r-and-rstudio-iglm02/ Fundamentals of populations genetics using R (FOPG01) 18 November 2020 - 27 November 2020 https://www.prstatistics.com/course/fundamentals-of-populations-genetics-using-r-fopg01/ Introduction to mixed models using R and Rstudio (IMMR03) 25 November 2020 - 26 November 2020 https://www.prstatistics.com/course/introduction-to-mixed-models-using-r-and-rstudio-immr03/ Introduction to Python (PYIN01) 25 November 2020 - 26 November 2020 https://www.prstatistics.com/course/introduction-to-python-pyin01/ Bayesian hierarchical modelling using R (IBHM05) 27 November 2020 - 11 December 2020 https://www.prstatistics.com/course/bayesian-hierarchical-modelling-using-r-ibhm05/ Meta-analysis in ecology, evolution and environmental sciences (METR01) 30 November 2020 - 4 December 2020 https://www.prstatistics.com/course/meta-analysis-in-ecology-evolution-and-environmental-sciences-metr01/ Introduction to Python for Scientific Computing (PYSC01) 2 December 2020 - 3 December 2020 https://www.prstatistics.com/course/introduction-to-python-for-scientific-computing-pysc01/ Machine Learning and Deep Learning using Python (PYML01) 9 December 2020 - 10 December 2020 https://www.prstatistics.com/course/machine-learning-and-deep-learning-using-python-pyml01/ Structural Equation Modelling for Ecologists and Evolutionary Biologists (SEMR03) This course will be delivered live 18th January 2021 - 22nd January 2021 https://www.prstatistics.com/course/structural-equation-modelling-for-ecologists-and-evolutionary-biologists-semr03/ Species Distribution Modeling using R (SDMR03) 25th January 2021 - 29th January 2021 https://www.prstatistics.com/course/species-distribution-modeling-using-r-sdmr03/ Advanced Ecological Niche Modelling Using R (ANMR01) 25th January 2021 - 29th January 2021 https://www.prstatistics.com/course/advanced-ecological-niche-modelling-using-r-anmr01/ -- Oliver Hooker PhD. PR statistics 2020 publications; Parallelism in eco-morphology and gene expression despite variable evolutionary and genomic backgrounds in a Holarctic fish. PLOS GENETICS (2020). IN PRESS www.PRstatistics.com facebook.com/PRstatistics/ twitter.com/PRstatistics 53 Morrison Street Glasgow G5 8LB +44 (0) 7966500340 +44 (0) 7966500340 _______________________________________________ MARMAM mailing list MARMAM@lists.uvic.ca https://lists.uvic.ca/mailman/listinfo/marmam
