[R-sig-dyn-mod] Time Series Analysis and Forecasting in R course

[i@io m@iii@g oii phys@ii@-courses@org]

Dear colleagues,
I would like to share information about an upcoming online training course that may be of interest to members of the r-sig-dynamic-models community: Time Series Analysis and Forecasting in R
 
Dates: 20–24 July

 
Course website: [ https://www.physalia-courses.org/courses-workshops/time-series-in-r/ ]( https://www.physalia-courses.org/courses-workshops/time-series-in-r/ ) 
 
This 5-day course focuses on advanced time series analysis and forecasting techniques. Unlike many traditional courses that emphasize classical models such as ARIMA or Exponential Smoothing, this course introduces powerful Bayesian dynamic models implemented in Stan via R packages like mvgam and brms. These tools allow modeling complex ecological time series with features such as overdispersion, clustering, missingness, discreteness, and nonlinear effects.
 
Topics covered include data wrangling and visualization, dynamic generalized linear and additive models (GLMs and GAMs), temporal autocorrelation, multivariate time series, and probabilistic forecasting and evaluation.
 
 
Best regards,
 
Carlo
 
 
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Carlo Pecoraro, Ph.D


Physalia-courses DIRECTOR

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