News:Course on Generalised Additive Models In R
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17 months ago
carlopecoraro2 ★ 2.5k

Dear all,

registration is now open for the 3rd edition of the course "Generalised Additive Models In R": https://www.physalia-courses.org/courses-workshops/gams-in-r/


Dates: online, March 20th-24th


The course is aimed at graduate students and researchers with some statistical knowledge; ideally, you'll know something about generalized linear models, likelihood, and AIC. However we’ll recap what GLMs are so if you’re a little rusty or not everything mentioned in the GLM course makes sense, we have you covered. From running the course previously, knowing the difference between "fixed" and "random" effects, and what the terms "random intercepts" and "random slopes" are, will be helpful for the Hierarchical GAM topic, but we don't expect you to be an expert in mixed effects or hierarchical models to take this course. Participants should be familiar with RStudio and have some fluency in programming R code, including importing, manipulating (e.g., modifying variables) and visualising data. There will be a mix of lectures, in-class discussions, and hands-on practical exercises along the course.


After completing this course, the participants will:

  1. Understand how GAMs work from a practical viewpoint to learn relationships between covariates and responses from the data
  2. Be able to fit GAMs in R using the mgcv and brms packages
  3. Know the differences between the types of splines and when to use them in your models
  4. Know how to visualise fitted GAMs and to check the assumptions of the model

Here is the complete list of our courses and Workshops in January:

  • Introduction to R Shiny - 10-11 January

  • Unix and Shell Scripting for Bioinformatics - 9-13 January

    • Flow cytometry analysis with R/Bioconductor - 16-19 January
  • Winter School in Bioinformatics - 16-19 January

  • Sex Chromosome Evolution - 23-27 January

  • Cancer Genomics in R - 23-27 January

  • Gene Set Enrichment Analysis in R/Bioconductor - 30 January- 2 February

Statistics GAMs R • 471 views
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