Compositional data (CoDa) are those which represent parts of some whole and which
only carry relative information. Typical examples are data presented in percentages,
ppm, ppb, or the like. Since John Aitchison introduced the log-ratio approach to analyse
CoDa back in 1982, much progress has been done in understanding the geometry peculiar
to their sample space, the D-part simplex. This one-and-a-half day short course presents
the state of the art in this field of active research and will cover the following topics:
- Hypothesis underlying statistical data analysis (sample space, scale).
- The Aitchison geometry of the simplex.
- Coordinate representation; distributions on the simplex.
- Exploratory analysis (centering, variation array, biplot, balances-dendrogram).
- Linear processes in the simplex; regression.
- Introduction to CoDaPack, a userfriendly freeware; discussion of case studies.
Instructors:
- Prof. Vera Pawlowsky-Glahn
- Prof. Juan José Egozcue
- Prof. Santiago Thió-Henestrosa
Recommended background:
- first semester courses in statistics, algebra and calculus;
- basic knowledge in multivariate statistics.
Attendants are encouraged to bring their own laptops for practicals. Excel (MicroSoft Office) should be available in the laptops.
If some assistant is unable to bring any laptop, this circumstance should be specified in the registration form.
Language of the course: English
Schedule: May 26: 10h-13h + lunch time+ 15h-18h
May 27: 10h-13h
Location: Building Politècnica 4 (P-IV), Campus Montilivi, Universitat de Girona
There are limited places on the course and participants to the workshop
will have preference to attend the course.