[R-sig-ME] Online Time Series Analysis course

[Alain Zuur]

Dear colleague,

We are pleased to announce our upcoming online live course:
Bayesian Time Series Analysis: GAMs, Random Walks and Hierarchical Time 
Series in inlabru

Dates: 7–11 September 2026
Times: 14.00–20.00 UK time
Instructors: Dr Alain F. Zuur and Dr Elena N. Ieno

This applied course introduces Bayesian time series analysis using 
generalised additive models and latent temporal structures in inlabru. 
We begin with regression, mixed-effects models and univariate time 
series before progressing to hierarchical and multivariate time series 
with shared and group-specific temporal trends.

The course covers continuous, count, presence–absence and proportional 
data. Topics include RW2 models, seasonality, long-term trends, 
covariate effects, random effects, irregularly spaced observations, 
common latent temporal drivers, posterior simulation and model validation.
All methods are taught through annotated R exercises using real 
ecological and environmental datasets. Participants receive 12 months’ 
access to the course website, including the exercises, supporting 
materials and on-demand videos.

The fee also includes a one-hour online meeting with one or both 
instructors to discuss your own data.

Further information and registration: 
https://www.highstat.com/index.php/joine-an-onsite-course

Please feel free to forward this announcement to colleagues who may be 
interested.


Kind regards,
Dr Alain F. Zuur
Highland Statistics Ltd
highstat using highstat.com
www.highstat.com