[Forum SIS] Politecnico di Milano - Seminario Eva Fiserova e Karel Hron

[Laura M. Sangalli]

Si avvisa che in data 06-04-2017, alle ore 14:00 precise,

presso l'Aula Seminari "F. Saleri" VI piano - Dipartimento di 
Matematica, Politecnico di Milano,

nell'ambito delle iniziative MOX, si svolgerà il seguente seminario:

Relatori:

Eva Fiserova e Karel Hron, Palacky University, Olomouc, Czech Republic

Titolo:

Regression analysis for compositional data from perspective of the 
logratio approach

Sommario:

Regression analysis is an important tool for analysing the relationships 
between the response variable and known explanatory variables. When the 
response variables or explanatory variables are compositional, i.e. 
multivariate observations carrying only relative information 
(proportions, percentages), a special treatment in regression is 
necessary. Compositional data are characterized by the simplex sample 
space with the Aitchison geometry that forms the Euclidean structure. 
Proper statistical methodology for this kind of observations is the 
logratio methodology that enables to express the data isometrically in 
the real Euclidean space where it is possible to apply standard 
statistical tools (Aitchison, 1986; Pawlowsky-Glahn et al., 2015). The 
lecture is focused on three main regression tasks, where compositional 
data are involved: either regression with a compositional response 
variable, or regression with compositional explanatory variables, or 
regression between parts of a composition. The main methodological 
approach for dealing with compositional regression is based on 
orthonormal logratio coordinates. Although regression models in 
orthonormal logratio coordinates are theoretically well justified, both 
the normalizing constants to reach orthonormality and the natural 
logarithm itself result in quite a complex interpretation of the 
regression parameters. In the lecture, we will present new orthogonal 
logratio coordinates (Muller et al., 2017) in order to achieve better 
interpretability of regression parameters while preserving all important 
features of regression models for compositional data. Theoretical 
results will be applied to real-world examples.

Docente di riferimento:

Alessandra Menafoglio, alessandra.menafoglio at polimi.it



Tutti gli interessati sono invitati a partecipare.

Cordiali saluti,

Laura Sangalli

-- 
Laura Maria Sangalli
MOX - Dipartimento di Matematica
Politecnico di Milano
Piazza Leonardo da Vinci 32
20133 Milano - Italy
tel: +39 02 2399 4554
fax: +39 02 2399 4568
email: laura.sangalli at polimi.it
url: http://mox.polimi.it/~sangalli

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