Bayesian Nonlinear Models for Ecologists (BNLM01) SOLD OUT!
Learn how to build, fit, and compare theory-driven nonlinear ecological models using Bayesian methods in R with brms.
Duration: 5 Days, 4.5 hours per day
Next Date: April 27-May 1, 2026
Format: Live Online Format
UK (GMT+1) local time - All sessions will be recorded and made available to ensure accessibility for attendees across different time zones.
£400Registration Fee
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5.0
from 200+ reviews
- Overview
- Instructors
- Schedule
Course Description
There are no straight lines in ecology. While we often use the linear model to approximate relationships between ecological variables, we usually have access to a more precise, more interpretable model. For example, a mechanistic model based on theory might be available for our system based on literature, or developed specifically for our system. However, many ecologists are not familiar with tools that would let them connect their datasets and nonlinear models.
The R package brms has made Bayesian modelling accessible via a flexible, general syntax. This gives ecologists the ability, in many cases, to fit exactly the model they wish to their data. In this workshop we’ll begin reviewing brms syntax for fitting simple linear model, and then look at nonlinear functions that are useful for a wide range of ecological challenges. This will include power laws for scaling relationships, predator-prey interactions, thermal performance curves, and more. We will discuss the process for building or selecting a model for a specific dataset, and will have time to practice these techniques on your own research questions.
What You’ll Learn
During the course we will cover the following:
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Brms syntax, including nonlinear syntax
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Setting priors for nonlinear models
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Finding, adapting, and writing your own nonlinear model
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How to compare nonlinear models when you have more than one candidate model
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Assessing model fit and communicating your results.
Course Format
Interactive Learning Format
Each day features a well-balanced combination of lectures and hands-on practical exercises, with dedicated time for discussing participants’ own data, time permitting.
Global Accessibility
All live sessions are recorded and made available on the same day, ensuring accessibility for participants across different time zones.
Collaborative Discussions
Open discussion sessions provide an opportunity for participants to explore specific research questions and engage with instructors and peers.
Comprehensive Course Materials
All code, datasets, and presentation slides used during the course will be shared with participants by the instructor.
Personalized Data Engagement
Participants are encouraged to bring their own data for discussion and practical application during the course.
Post-Course Support
Participants will receive continued support via email for 30 days following the course, along with on-demand access to session recordings for the same period.
Who Should Attend / Intended Audiences
Coming soon…
Equipment and Software requirements
A laptop or desktop computer with a functioning installation of R and RStudio is required. Both R and RStudio are free, open-source programs compatible with Windows, macOS, and Linux systems.
A working webcam is recommended to support interactive elements of the course. We encourage participants to keep their cameras on during live Zoom sessions to foster a more engaging and collaborative environment.
While not essential, using a large monitor—or ideally a dual-monitor setup—can significantly enhance your learning experience by allowing you to view course materials and work in R simultaneously.
Dr Andrew MacDonald
Andrew is a community ecologist and entomologist, and an applied statistician also. It is the passion for learning, practicing, and talking about statistics that led him into collaborations with scientists from many different fields. Andrew has extensive experience in collaboration and consulting, and now has experience building statistical models of animal behaviour, community composition, occupancy modelling, tree growth, and survey data from humans – to name just a few. He’s especially passionate about helping ecologists connect their theories and their data through expressive statistical models. His favourite tools to do this with are R, brms, and Stan. His goal is to improve our ability to make predictions for ecological systems, and to build a community of practice around statistical methods in ecology.
Education & Career
• PhD in Zoology (Experimental community ecology)
• MSc in Botany (Invasive species ecology)
• Instructor and consultant on a wide range of ecological topics.
Teaching & Skills
• Teaching topics including GLMs, nonlinear models, and hierarchical models – usually with a Bayesian perspective.
• Training and advice regarding reproducible workflows and open science.
• Experienced in collaboration and in developing statistical methods to combine theory with a specific dataset.
Links
Google scholar
Session 1 – 02:00:00 – Using simulations and plots, reviewing basic parts of a model including factors, contrasts, and linear interactions.
Break – 00:30:00
Session 2 – 02:00:00 – Model diagnostic plots
Session 3 – 02:00:00 – Introduction to Bayesian thinking, and contrasting rstanarm with lme4, Simulating random intercept models
Break – 00:30:00
Session 4 – 02:00:00 – Plotting predictions for models with and without random intercepts.
Session 5 – 02:00:00 – Response distributions, and how to select one, Link functions, and how they change model outputs.
Break – 00:30:00
Session 6 – 02:00:00 – Plotting predictions and conditional effects from models.
Session 7 – 02:00:00 – Making predictions for random effects.
Break – 00:30:00
Session 8 – 02:00:00 – Analyzing designed experiments, including ANOVA, ANCOVA , and t-tests.
Session 9 – 02:00:00 – How to publish a model, Modelling Zero-inflated and overdispersed outcomes.
Break – 00:30:00
Session 10 – 02:00:00 – Working on independent projects.
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Testimonials
PRStats offers a great lineup of courses on statistical and analytical methods that are super relevant for ecologists and biologists. My lab and I have taken several of their courses—like Bayesian mixing models, time series analysis, and machine/deep learning—and we've found them very informative and directly useful for our work. I often recommend PRStats to my students and colleagues as a great way to brush up on or learn new R-based statistical skills.
Rolando O. Santos
PhD Assistant Professor, Florida International University
Courses attended
SIMM05, IMDL03, ITSA02, GEEE01 and MOVE07
Frequently asked questions
Everything you need to know about the product and billing.
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
When will I receive instructions on how to join?
You’ll receive an email on the Friday before the course begins, with full instructions on how to join via Zoom. Please ensure you have Zoom installed in advance.
Do I need administrator rights on my computer?
I’m attending the course live — will I also get access to the session recordings?
I can’t attend every live session — can I join some sessions live and catch up on others later?
I’m in a different time zone and plan to follow the course via recordings. When will these be available?
I can’t attend live — how can I ask questions?
Will I receive a certificate?
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