Introduction to Compositional Data Analysis and Modelling

Prof. Fabio Divino
Università del Molise & University of Jyväskylä

Abstract

This course introduces the fundamental concepts of compositional data analysis, including the algebraic structure of the simplex and its main properties. It will then cover the basic tools for analysis before presenting the main regression models:
(a) compositional data as a predictor;
(b) compositional data as a response variable;
(c) compositional data as both predictor and response.

All topics will be explored through hands-on lab sessions in R using real data and simulations.

Outline

• Lecture 1: Introduction to Compositional Data Analysis. ALR, ILR, and CLR Transformations
• Lecture 2: Descriptive Analysis in the Simplex. Introduction to Regression Models
• Lecture 3: Regression Models with Compositional Data

Schedule

The course consists of a total of 6 hours, scheduled as follows:

• March 17, 15:00-17:00 – Aula A
• March 19, 11:00-13:00 – Aula A
• March 21, 15:00-17:00 – Aula A

Exam

The final exam consists of a presentation on a specific topic covered in the course.

References

• K. Gerald van den Boogaart & Raimon Tolosana-Delgado, Analyzing Compositional Data with R, Springer, 2013.