[R-sig-eco] Species distribution modelling with Bayesian statistics in R (SDMB01)

[Oliver Hooker]

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. Unlike most other SDM methods, 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). 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 oliverhooker using 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

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